Overview

Dataset statistics

Number of variables59
Number of observations49
Missing cells1062
Missing cells (%)36.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory22.7 KiB
Average record size in memory474.6 B

Variable types

Numeric11
Categorical39
Unsupported9

Alerts

type has constant value "regular" Constant
airdate has constant value "2020-12-19" Constant
_embedded.show.externals.tvrage has constant value "15090.0" Constant
id is highly correlated with rating.average and 2 other fieldsHigh correlation
season is highly correlated with _embedded.show.rating.average and 1 other fieldsHigh correlation
number is highly correlated with rating.average and 1 other fieldsHigh correlation
runtime is highly correlated with rating.average and 3 other fieldsHigh correlation
rating.average is highly correlated with id and 10 other fieldsHigh correlation
_embedded.show.id is highly correlated with id and 5 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with runtime and 3 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with runtime and 3 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with season and 3 other fieldsHigh correlation
_embedded.show.weight is highly correlated with rating.average and 2 other fieldsHigh correlation
_embedded.show.webChannel.id is highly correlated with rating.average and 1 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with season and 3 other fieldsHigh correlation
_embedded.show.updated is highly correlated with rating.average and 1 other fieldsHigh correlation
_embedded.show.network.id is highly correlated with id and 8 other fieldsHigh correlation
id is highly correlated with rating.averageHigh correlation
season is highly correlated with runtime and 2 other fieldsHigh correlation
runtime is highly correlated with season and 3 other fieldsHigh correlation
rating.average is highly correlated with id and 2 other fieldsHigh correlation
_embedded.show.id is highly correlated with _embedded.show.rating.average and 2 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with season and 3 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with season and 3 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with rating.average and 4 other fieldsHigh correlation
_embedded.show.weight is highly correlated with _embedded.show.id and 1 other fieldsHigh correlation
_embedded.show.webChannel.id is highly correlated with _embedded.show.network.idHigh correlation
_embedded.show.externals.thetvdb is highly correlated with _embedded.show.id and 1 other fieldsHigh correlation
_embedded.show.updated is highly correlated with rating.average and 1 other fieldsHigh correlation
_embedded.show.network.id is highly correlated with runtime and 3 other fieldsHigh correlation
id is highly correlated with rating.averageHigh correlation
season is highly correlated with _embedded.show.rating.average and 1 other fieldsHigh correlation
runtime is highly correlated with _embedded.show.runtime and 2 other fieldsHigh correlation
rating.average is highly correlated with id and 1 other fieldsHigh correlation
_embedded.show.id is highly correlated with _embedded.show.rating.average and 1 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with runtime and 2 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with runtime and 2 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with season and 3 other fieldsHigh correlation
_embedded.show.weight is highly correlated with _embedded.show.id and 1 other fieldsHigh correlation
_embedded.show.webChannel.id is highly correlated with _embedded.show.network.idHigh correlation
_embedded.show.externals.thetvdb is highly correlated with seasonHigh correlation
_embedded.show.network.id is highly correlated with runtime and 3 other fieldsHigh correlation
id is highly correlated with url and 31 other fieldsHigh correlation
url is highly correlated with id and 45 other fieldsHigh correlation
name is highly correlated with id and 44 other fieldsHigh correlation
season is highly correlated with url and 21 other fieldsHigh correlation
number is highly correlated with id and 25 other fieldsHigh correlation
airtime is highly correlated with id and 33 other fieldsHigh correlation
airstamp is highly correlated with id and 38 other fieldsHigh correlation
runtime is highly correlated with url and 27 other fieldsHigh correlation
summary is highly correlated with id and 35 other fieldsHigh correlation
rating.average is highly correlated with url and 24 other fieldsHigh correlation
_links.self.href is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show.id is highly correlated with url and 30 other fieldsHigh correlation
_embedded.show.url is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show.name is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show.type is highly correlated with url and 34 other fieldsHigh correlation
_embedded.show.language is highly correlated with id and 31 other fieldsHigh correlation
_embedded.show.status is highly correlated with url and 27 other fieldsHigh correlation
_embedded.show.runtime is highly correlated with url and 30 other fieldsHigh correlation
_embedded.show.averageRuntime is highly correlated with url and 31 other fieldsHigh correlation
_embedded.show.premiered is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show.ended is highly correlated with id and 33 other fieldsHigh correlation
_embedded.show.officialSite is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show.schedule.time is highly correlated with url and 35 other fieldsHigh correlation
_embedded.show.rating.average is highly correlated with id and 31 other fieldsHigh correlation
_embedded.show.weight is highly correlated with url and 27 other fieldsHigh correlation
_embedded.show.webChannel.id is highly correlated with id and 31 other fieldsHigh correlation
_embedded.show.webChannel.name is highly correlated with id and 38 other fieldsHigh correlation
_embedded.show.webChannel.country.name is highly correlated with id and 29 other fieldsHigh correlation
_embedded.show.webChannel.country.code is highly correlated with id and 29 other fieldsHigh correlation
_embedded.show.webChannel.country.timezone is highly correlated with id and 29 other fieldsHigh correlation
_embedded.show.webChannel.officialSite is highly correlated with id and 33 other fieldsHigh correlation
_embedded.show.externals.thetvdb is highly correlated with url and 23 other fieldsHigh correlation
_embedded.show.externals.imdb is highly correlated with id and 38 other fieldsHigh correlation
_embedded.show.image.medium is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show.image.original is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show.summary is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show.updated is highly correlated with id and 33 other fieldsHigh correlation
_embedded.show._links.self.href is highly correlated with id and 45 other fieldsHigh correlation
_embedded.show._links.previousepisode.href is highly correlated with id and 45 other fieldsHigh correlation
image.medium is highly correlated with id and 38 other fieldsHigh correlation
image.original is highly correlated with id and 38 other fieldsHigh correlation
_embedded.show._links.nextepisode.href is highly correlated with id and 31 other fieldsHigh correlation
_embedded.show.network.id is highly correlated with id and 27 other fieldsHigh correlation
_embedded.show.network.name is highly correlated with id and 27 other fieldsHigh correlation
_embedded.show.network.country.name is highly correlated with url and 17 other fieldsHigh correlation
_embedded.show.network.country.code is highly correlated with url and 17 other fieldsHigh correlation
_embedded.show.network.country.timezone is highly correlated with url and 17 other fieldsHigh correlation
runtime has 4 (8.2%) missing values Missing
image has 49 (100.0%) missing values Missing
summary has 39 (79.6%) missing values Missing
rating.average has 46 (93.9%) missing values Missing
_embedded.show.runtime has 13 (26.5%) missing values Missing
_embedded.show.averageRuntime has 5 (10.2%) missing values Missing
_embedded.show.ended has 30 (61.2%) missing values Missing
_embedded.show.officialSite has 4 (8.2%) missing values Missing
_embedded.show.rating.average has 42 (85.7%) missing values Missing
_embedded.show.network has 49 (100.0%) missing values Missing
_embedded.show.webChannel.id has 1 (2.0%) missing values Missing
_embedded.show.webChannel.name has 1 (2.0%) missing values Missing
_embedded.show.webChannel.country.name has 23 (46.9%) missing values Missing
_embedded.show.webChannel.country.code has 23 (46.9%) missing values Missing
_embedded.show.webChannel.country.timezone has 23 (46.9%) missing values Missing
_embedded.show.webChannel.officialSite has 26 (53.1%) missing values Missing
_embedded.show.dvdCountry has 49 (100.0%) missing values Missing
_embedded.show.externals.tvrage has 48 (98.0%) missing values Missing
_embedded.show.externals.thetvdb has 12 (24.5%) missing values Missing
_embedded.show.externals.imdb has 27 (55.1%) missing values Missing
_embedded.show.image.medium has 3 (6.1%) missing values Missing
_embedded.show.image.original has 3 (6.1%) missing values Missing
_embedded.show.summary has 4 (8.2%) missing values Missing
image.medium has 34 (69.4%) missing values Missing
image.original has 34 (69.4%) missing values Missing
_embedded.show._links.nextepisode.href has 44 (89.8%) missing values Missing
_embedded.show.image has 49 (100.0%) missing values Missing
_embedded.show.webChannel.country has 49 (100.0%) missing values Missing
_embedded.show.network.id has 46 (93.9%) missing values Missing
_embedded.show.network.name has 46 (93.9%) missing values Missing
_embedded.show.network.country.name has 46 (93.9%) missing values Missing
_embedded.show.network.country.code has 46 (93.9%) missing values Missing
_embedded.show.network.country.timezone has 46 (93.9%) missing values Missing
_embedded.show.network.officialSite has 49 (100.0%) missing values Missing
_embedded.show.webChannel has 49 (100.0%) missing values Missing
url is uniformly distributed Uniform
name is uniformly distributed Uniform
summary is uniformly distributed Uniform
rating.average is uniformly distributed Uniform
_links.self.href is uniformly distributed Uniform
_embedded.show.url is uniformly distributed Uniform
_embedded.show.name is uniformly distributed Uniform
_embedded.show.premiered is uniformly distributed Uniform
_embedded.show.officialSite is uniformly distributed Uniform
_embedded.show.externals.imdb is uniformly distributed Uniform
_embedded.show.image.medium is uniformly distributed Uniform
_embedded.show.image.original is uniformly distributed Uniform
_embedded.show.summary is uniformly distributed Uniform
_embedded.show._links.self.href is uniformly distributed Uniform
_embedded.show._links.previousepisode.href is uniformly distributed Uniform
image.medium is uniformly distributed Uniform
image.original is uniformly distributed Uniform
_embedded.show._links.nextepisode.href is uniformly distributed Uniform
_embedded.show.network.id is uniformly distributed Uniform
_embedded.show.network.name is uniformly distributed Uniform
id has unique values Unique
url has unique values Unique
_links.self.href has unique values Unique
image is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.genres is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.schedule.days is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.network is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.dvdCountry is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.image is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.webChannel.country is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.network.officialSite is an unsupported type, check if it needs cleaning or further analysis Unsupported
_embedded.show.webChannel is an unsupported type, check if it needs cleaning or further analysis Unsupported

Reproduction

Analysis started2022-09-06 02:45:21.863974
Analysis finished2022-09-06 02:45:35.097903
Duration13.23 seconds
Software versionpandas-profiling v3.2.0
Download configurationconfig.json

Variables

id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
UNIQUE

Distinct49
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2063413.245
Minimum1943281
Maximum2386108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size520.0 B
2022-09-05T21:45:35.182790image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1943281
5-th percentile1956788.6
Q11984914
median1997521
Q32118378
95-th percentile2308144.8
Maximum2386108
Range442827
Interquartile range (IQR)133464

Descriptive statistics

Standard deviation117489.1214
Coefficient of variation (CV)0.05693921065
Kurtosis0.5194823158
Mean2063413.245
Median Absolute Deviation (MAD)36233
Skewness1.274938781
Sum101107249
Variance1.380369365 × 1010
MonotonicityNot monotonic
2022-09-05T21:45:35.295195image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
19888621
 
2.0%
19885961
 
2.0%
19975201
 
2.0%
19975211
 
2.0%
20000641
 
2.0%
20000651
 
2.0%
20311921
 
2.0%
20399371
 
2.0%
21183781
 
2.0%
21817971
 
2.0%
Other values (39)39
79.6%
ValueCountFrequency (%)
19432811
2.0%
19530701
2.0%
19537891
2.0%
19612881
2.0%
19620581
2.0%
19725711
2.0%
19725721
2.0%
19773271
2.0%
19832741
2.0%
19841811
2.0%
ValueCountFrequency (%)
23861081
2.0%
23181071
2.0%
23112141
2.0%
23035411
2.0%
22898741
2.0%
22893241
2.0%
22121671
2.0%
21821181
2.0%
21817971
2.0%
21761361
2.0%

url
Categorical

HIGH CORRELATION
UNIFORM
UNIQUE

Distinct49
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size520.0 B
https://www.tvmaze.com/episodes/1988862/sim-for-you-4x24-chanyeols-episode-24
 
1
https://www.tvmaze.com/episodes/1988596/detention-1x06-re-detention
 
1
https://www.tvmaze.com/episodes/1997520/the-penalty-zone-1x13-episode-13
 
1
https://www.tvmaze.com/episodes/1997521/the-penalty-zone-1x14-episode-14
 
1
https://www.tvmaze.com/episodes/2000064/ultimate-note-1x17-episode-17
 
1
Other values (44)
44 

Length

Max length122
Median length90
Mean length81.69387755
Min length53

Characters and Unicode

Total characters4003
Distinct characters40
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique49 ?
Unique (%)100.0%

Sample

1st rowhttps://www.tvmaze.com/episodes/1988862/sim-for-you-4x24-chanyeols-episode-24
2nd rowhttps://www.tvmaze.com/episodes/1989501/troe-iz-prostokvasino-2x39-papa-ne-goruj
3rd rowhttps://www.tvmaze.com/episodes/1989503/troe-iz-prostokvasino-2x40-sneznyj-labirint
4th rowhttps://www.tvmaze.com/episodes/1988697/soul-land-7x05-di135ji
5th rowhttps://www.tvmaze.com/episodes/2386108/xian-feng-jian-yu-lu-1x49-episode-49

Common Values

ValueCountFrequency (%)
https://www.tvmaze.com/episodes/1988862/sim-for-you-4x24-chanyeols-episode-241
 
2.0%
https://www.tvmaze.com/episodes/1988596/detention-1x06-re-detention1
 
2.0%
https://www.tvmaze.com/episodes/1997520/the-penalty-zone-1x13-episode-131
 
2.0%
https://www.tvmaze.com/episodes/1997521/the-penalty-zone-1x14-episode-141
 
2.0%
https://www.tvmaze.com/episodes/2000064/ultimate-note-1x17-episode-171
 
2.0%
https://www.tvmaze.com/episodes/2000065/ultimate-note-1x18-episode-181
 
2.0%
https://www.tvmaze.com/episodes/2031192/our-memory-1x03-episode-31
 
2.0%
https://www.tvmaze.com/episodes/2039937/tregayes-way-in-the-kitchen-1x06-soul-food-sunday1
 
2.0%
https://www.tvmaze.com/episodes/2118378/yaar-jigree-kasooti-degree-2x12-cracked1
 
2.0%
https://www.tvmaze.com/episodes/2181797/i-like-to-watch-3x09-dolly-partons-christmas-on-the-square1
 
2.0%
Other values (39)39
79.6%

Length

2022-09-05T21:45:35.410139image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.tvmaze.com/episodes/1988862/sim-for-you-4x24-chanyeols-episode-241
 
2.0%
https://www.tvmaze.com/episodes/1989501/troe-iz-prostokvasino-2x39-papa-ne-goruj1
 
2.0%
https://www.tvmaze.com/episodes/1989503/troe-iz-prostokvasino-2x40-sneznyj-labirint1
 
2.0%
https://www.tvmaze.com/episodes/1988697/soul-land-7x05-di135ji1
 
2.0%
https://www.tvmaze.com/episodes/2386108/xian-feng-jian-yu-lu-1x49-episode-491
 
2.0%
https://www.tvmaze.com/episodes/2138926/tokyo-joshi-pro-wrestling-2020-12-19-tjpw-seno-merry-christmas-20201
 
2.0%
https://www.tvmaze.com/episodes/1962058/heaven-officials-blessing-1x09-evil-taoist-scourge1
 
2.0%
https://www.tvmaze.com/episodes/1972571/the-wolf-1x29-episode-291
 
2.0%
https://www.tvmaze.com/episodes/1972572/the-wolf-1x30-episode-301
 
2.0%
https://www.tvmaze.com/episodes/2071487/youths-in-the-breeze-1x17-full-time-sworn-enemy-011
 
2.0%
Other values (39)39
79.6%

Most occurring characters

ValueCountFrequency (%)
e330
 
8.2%
-318
 
7.9%
t251
 
6.3%
s250
 
6.2%
/245
 
6.1%
o222
 
5.5%
w172
 
4.3%
i164
 
4.1%
1143
 
3.6%
a142
 
3.5%
Other values (30)1766
44.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2708
67.6%
Decimal Number585
 
14.6%
Other Punctuation392
 
9.8%
Dash Punctuation318
 
7.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e330
12.2%
t251
 
9.3%
s250
 
9.2%
o222
 
8.2%
w172
 
6.4%
i164
 
6.1%
a142
 
5.2%
p141
 
5.2%
m139
 
5.1%
d110
 
4.1%
Other values (16)787
29.1%
Decimal Number
ValueCountFrequency (%)
1143
24.4%
287
14.9%
073
12.5%
966
11.3%
857
 
9.7%
338
 
6.5%
737
 
6.3%
531
 
5.3%
430
 
5.1%
623
 
3.9%
Other Punctuation
ValueCountFrequency (%)
/245
62.5%
.98
 
25.0%
:49
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-318
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2708
67.6%
Common1295
32.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e330
12.2%
t251
 
9.3%
s250
 
9.2%
o222
 
8.2%
w172
 
6.4%
i164
 
6.1%
a142
 
5.2%
p141
 
5.2%
m139
 
5.1%
d110
 
4.1%
Other values (16)787
29.1%
Common
ValueCountFrequency (%)
-318
24.6%
/245
18.9%
1143
11.0%
.98
 
7.6%
287
 
6.7%
073
 
5.6%
966
 
5.1%
857
 
4.4%
:49
 
3.8%
338
 
2.9%
Other values (4)121
 
9.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII4003
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e330
 
8.2%
-318
 
7.9%
t251
 
6.3%
s250
 
6.2%
/245
 
6.1%
o222
 
5.5%
w172
 
4.3%
i164
 
4.1%
1143
 
3.6%
a142
 
3.5%
Other values (30)1766
44.1%

name
Categorical

HIGH CORRELATION
UNIFORM

Distinct48
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Memory size520.0 B
Episode 3
 
2
Chanyeol's Episode 24
 
1
Re: Detention
 
1
Episode 13
 
1
Episode 14
 
1
Other values (43)
43 

Length

Max length70
Median length30
Mean length19.40816327
Min length3

Characters and Unicode

Total characters951
Distinct characters114
Distinct categories8 ?
Distinct scripts5 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique47 ?
Unique (%)95.9%

Sample

1st rowChanyeol's Episode 24
2nd rowПапа, не горюй
3rd rowСнежный лабиринт
4th row第135集
5th rowEpisode 49

Common Values

ValueCountFrequency (%)
Episode 32
 
4.1%
Chanyeol's Episode 241
 
2.0%
Re: Detention1
 
2.0%
Episode 131
 
2.0%
Episode 141
 
2.0%
Episode 171
 
2.0%
Episode 181
 
2.0%
Soul Food Sunday1
 
2.0%
CRACKED1
 
2.0%
Dolly Parton's Christmas on the Square1
 
2.0%
Other values (38)38
77.6%

Length

2022-09-05T21:45:35.522882image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
episode13
 
7.9%
the5
 
3.0%
193
 
1.8%
christmas3
 
1.8%
december2
 
1.2%
neal2
 
1.2%
2
 
1.2%
enemy2
 
1.2%
sworn2
 
1.2%
full-time2
 
1.2%
Other values (120)129
78.2%

Most occurring characters

ValueCountFrequency (%)
116
 
12.2%
e67
 
7.0%
o50
 
5.3%
i48
 
5.0%
s44
 
4.6%
a35
 
3.7%
t34
 
3.6%
r33
 
3.5%
n31
 
3.3%
d30
 
3.2%
Other values (104)463
48.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter582
61.2%
Uppercase Letter152
 
16.0%
Space Separator116
 
12.2%
Decimal Number56
 
5.9%
Other Punctuation26
 
2.7%
Other Letter14
 
1.5%
Dash Punctuation3
 
0.3%
Math Symbol2
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e67
 
11.5%
o50
 
8.6%
i48
 
8.2%
s44
 
7.6%
a35
 
6.0%
t34
 
5.8%
r33
 
5.7%
n31
 
5.3%
d30
 
5.2%
p22
 
3.8%
Other values (39)188
32.3%
Uppercase Letter
ValueCountFrequency (%)
E22
14.5%
F12
 
7.9%
S11
 
7.2%
T10
 
6.6%
C10
 
6.6%
N9
 
5.9%
R8
 
5.3%
D8
 
5.3%
M7
 
4.6%
P7
 
4.6%
Other values (19)48
31.6%
Other Letter
ValueCountFrequency (%)
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
Other values (4)4
28.6%
Decimal Number
ValueCountFrequency (%)
116
28.6%
07
12.5%
27
12.5%
97
12.5%
36
 
10.7%
84
 
7.1%
44
 
7.1%
53
 
5.4%
61
 
1.8%
71
 
1.8%
Other Punctuation
ValueCountFrequency (%)
,6
23.1%
:5
19.2%
.4
15.4%
!3
11.5%
"2
 
7.7%
#2
 
7.7%
?2
 
7.7%
'2
 
7.7%
Math Symbol
ValueCountFrequency (%)
|1
50.0%
~1
50.0%
Space Separator
ValueCountFrequency (%)
116
100.0%
Dash Punctuation
ValueCountFrequency (%)
-3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin648
68.1%
Common203
 
21.3%
Cyrillic86
 
9.0%
Hangul12
 
1.3%
Han2
 
0.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e67
 
10.3%
o50
 
7.7%
i48
 
7.4%
s44
 
6.8%
a35
 
5.4%
t34
 
5.2%
r33
 
5.1%
n31
 
4.8%
d30
 
4.6%
p22
 
3.4%
Other values (38)254
39.2%
Cyrillic
ValueCountFrequency (%)
и9
 
10.5%
н7
 
8.1%
а6
 
7.0%
о6
 
7.0%
е5
 
5.8%
р5
 
5.8%
к4
 
4.7%
с3
 
3.5%
д3
 
3.5%
й3
 
3.5%
Other values (20)35
40.7%
Common
ValueCountFrequency (%)
116
57.1%
116
 
7.9%
07
 
3.4%
27
 
3.4%
97
 
3.4%
,6
 
3.0%
36
 
3.0%
:5
 
2.5%
84
 
2.0%
44
 
2.0%
Other values (12)25
 
12.3%
Hangul
ValueCountFrequency (%)
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
Other values (2)2
16.7%
Han
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII850
89.4%
Cyrillic86
 
9.0%
Hangul12
 
1.3%
CJK2
 
0.2%
None1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
116
 
13.6%
e67
 
7.9%
o50
 
5.9%
i48
 
5.6%
s44
 
5.2%
a35
 
4.1%
t34
 
4.0%
r33
 
3.9%
n31
 
3.6%
d30
 
3.5%
Other values (59)362
42.6%
Cyrillic
ValueCountFrequency (%)
и9
 
10.5%
н7
 
8.1%
а6
 
7.0%
о6
 
7.0%
е5
 
5.8%
р5
 
5.8%
к4
 
4.7%
с3
 
3.5%
д3
 
3.5%
й3
 
3.5%
Other values (20)35
40.7%
None
ValueCountFrequency (%)
å1
100.0%
Hangul
ValueCountFrequency (%)
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
Other values (2)2
16.7%
CJK
ValueCountFrequency (%)
1
50.0%
1
50.0%

season
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct9
Distinct (%)18.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean290.3469388
Minimum1
Maximum2020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size520.0 B
2022-09-05T21:45:35.606046image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q34
95-th percentile2020
Maximum2020
Range2019
Interquartile range (IQR)3

Descriptive statistics

Standard deviation713.4474271
Coefficient of variation (CV)2.457223865
Kurtosis2.538334026
Mean290.3469388
Median Absolute Deviation (MAD)0
Skewness2.106251505
Sum14227
Variance509007.2313
MonotonicityNot monotonic
2022-09-05T21:45:35.688215image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
126
53.1%
20207
 
14.3%
25
 
10.2%
34
 
8.2%
42
 
4.1%
52
 
4.1%
71
 
2.0%
81
 
2.0%
61
 
2.0%
ValueCountFrequency (%)
126
53.1%
25
 
10.2%
34
 
8.2%
42
 
4.1%
52
 
4.1%
61
 
2.0%
71
 
2.0%
81
 
2.0%
20207
 
14.3%
ValueCountFrequency (%)
20207
 
14.3%
81
 
2.0%
71
 
2.0%
61
 
2.0%
52
 
4.1%
42
 
4.1%
34
 
8.2%
25
 
10.2%
126
53.1%

number
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION

Distinct27
Distinct (%)55.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24.24489796
Minimum3
Maximum346
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size520.0 B
2022-09-05T21:45:35.779571image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile4.4
Q17
median14
Q319
95-th percentile52.2
Maximum346
Range343
Interquartile range (IQR)12

Descriptive statistics

Standard deviation48.99682414
Coefficient of variation (CV)2.02091278
Kurtosis40.72665561
Mean24.24489796
Median Absolute Deviation (MAD)7
Skewness6.145140472
Sum1188
Variance2400.688776
MonotonicityNot monotonic
2022-09-05T21:45:35.876240image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
55
 
10.2%
64
 
8.2%
173
 
6.1%
183
 
6.1%
93
 
6.1%
123
 
6.1%
193
 
6.1%
32
 
4.1%
82
 
4.1%
142
 
4.1%
Other values (17)19
38.8%
ValueCountFrequency (%)
32
 
4.1%
41
 
2.0%
55
10.2%
64
8.2%
71
 
2.0%
82
 
4.1%
93
6.1%
102
 
4.1%
123
6.1%
131
 
2.0%
ValueCountFrequency (%)
3461
2.0%
541
2.0%
531
2.0%
511
2.0%
491
2.0%
441
2.0%
401
2.0%
391
2.0%
302
4.1%
291
2.0%

type
Categorical

CONSTANT
REJECTED

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size520.0 B
regular
49 

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters343
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowregular
2nd rowregular
3rd rowregular
4th rowregular
5th rowregular

Common Values

ValueCountFrequency (%)
regular49
100.0%

Length

2022-09-05T21:45:35.961146image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:45:36.035889image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
regular49
100.0%

Most occurring characters

ValueCountFrequency (%)
r98
28.6%
e49
14.3%
g49
14.3%
u49
14.3%
l49
14.3%
a49
14.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter343
100.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r98
28.6%
e49
14.3%
g49
14.3%
u49
14.3%
l49
14.3%
a49
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin343
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
r98
28.6%
e49
14.3%
g49
14.3%
u49
14.3%
l49
14.3%
a49
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII343
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
r98
28.6%
e49
14.3%
g49
14.3%
u49
14.3%
l49
14.3%
a49
14.3%

airdate
Categorical

CONSTANT
REJECTED

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size520.0 B
2020-12-19
49 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters490
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-12-19
2nd row2020-12-19
3rd row2020-12-19
4th row2020-12-19
5th row2020-12-19

Common Values

ValueCountFrequency (%)
2020-12-1949
100.0%

Length

2022-09-05T21:45:36.100732image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:45:36.172219image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
2020-12-1949
100.0%

Most occurring characters

ValueCountFrequency (%)
2147
30.0%
098
20.0%
-98
20.0%
198
20.0%
949
 
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number392
80.0%
Dash Punctuation98
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2147
37.5%
098
25.0%
198
25.0%
949
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-98
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common490
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2147
30.0%
098
20.0%
-98
20.0%
198
20.0%
949
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII490
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2147
30.0%
098
20.0%
-98
20.0%
198
20.0%
949
 
10.0%

airtime
Categorical

HIGH CORRELATION

Distinct13
Distinct (%)26.5%
Missing0
Missing (%)0.0%
Memory size520.0 B
34 
06:00
 
2
10:00
 
2
11:00
 
2
12:00
 
1
Other values (8)

Length

Max length5
Median length0
Mean length1.530612245
Min length0

Characters and Unicode

Total characters75
Distinct characters8
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)18.4%

Sample

1st row06:00
2nd row
3rd row
4th row10:00
5th row10:00

Common Values

ValueCountFrequency (%)
34
69.4%
06:002
 
4.1%
10:002
 
4.1%
11:002
 
4.1%
12:001
 
2.0%
05:001
 
2.0%
17:001
 
2.0%
18:001
 
2.0%
00:001
 
2.0%
00:151
 
2.0%
Other values (3)3
 
6.1%

Length

2022-09-05T21:45:36.244582image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
06:002
13.3%
10:002
13.3%
11:002
13.3%
12:001
6.7%
05:001
6.7%
17:001
6.7%
18:001
6.7%
00:001
6.7%
00:151
6.7%
21:501
6.7%
Other values (2)2
13.3%

Most occurring characters

ValueCountFrequency (%)
036
48.0%
:15
20.0%
112
 
16.0%
24
 
5.3%
63
 
4.0%
53
 
4.0%
71
 
1.3%
81
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number60
80.0%
Other Punctuation15
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
036
60.0%
112
 
20.0%
24
 
6.7%
63
 
5.0%
53
 
5.0%
71
 
1.7%
81
 
1.7%
Other Punctuation
ValueCountFrequency (%)
:15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common75
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
036
48.0%
:15
20.0%
112
 
16.0%
24
 
5.3%
63
 
4.0%
53
 
4.0%
71
 
1.3%
81
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII75
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
036
48.0%
:15
20.0%
112
 
16.0%
24
 
5.3%
63
 
4.0%
53
 
4.0%
71
 
1.3%
81
 
1.3%

airstamp
Categorical

HIGH CORRELATION

Distinct18
Distinct (%)36.7%
Missing0
Missing (%)0.0%
Memory size520.0 B
2020-12-19T12:00:00+00:00
20 
2020-12-19T04:00:00+00:00
2020-12-19T17:00:00+00:00
2020-12-19T11:00:00+00:00
 
2
2020-12-19T02:00:00+00:00
 
2
Other values (13)
15 

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters1225
Distinct characters14
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)22.4%

Sample

1st row2020-12-18T21:00:00+00:00
2nd row2020-12-19T00:00:00+00:00
3rd row2020-12-19T00:00:00+00:00
4th row2020-12-19T02:00:00+00:00
5th row2020-12-19T02:00:00+00:00

Common Values

ValueCountFrequency (%)
2020-12-19T12:00:00+00:0020
40.8%
2020-12-19T04:00:00+00:005
 
10.2%
2020-12-19T17:00:00+00:005
 
10.2%
2020-12-19T11:00:00+00:002
 
4.1%
2020-12-19T02:00:00+00:002
 
4.1%
2020-12-19T03:00:00+00:002
 
4.1%
2020-12-19T00:00:00+00:002
 
4.1%
2020-12-19T15:15:00+00:001
 
2.0%
2020-12-19T21:00:00+00:001
 
2.0%
2020-12-19T20:50:00+00:001
 
2.0%
Other values (8)8
 
16.3%

Length

2022-09-05T21:45:36.344111image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-12-19t12:00:00+00:0020
40.8%
2020-12-19t17:00:00+00:005
 
10.2%
2020-12-19t04:00:00+00:005
 
10.2%
2020-12-19t11:00:00+00:002
 
4.1%
2020-12-19t02:00:00+00:002
 
4.1%
2020-12-19t03:00:00+00:002
 
4.1%
2020-12-19t00:00:00+00:002
 
4.1%
2020-12-19t15:00:00+00:001
 
2.0%
2020-12-19t05:00:00+00:001
 
2.0%
2020-12-19t07:00:00+00:001
 
2.0%
Other values (8)8
 
16.3%

Most occurring characters

ValueCountFrequency (%)
0507
41.4%
2173
 
14.1%
:147
 
12.0%
1132
 
10.8%
-98
 
8.0%
T49
 
4.0%
+49
 
4.0%
948
 
3.9%
76
 
0.5%
45
 
0.4%
Other values (4)11
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number882
72.0%
Other Punctuation147
 
12.0%
Dash Punctuation98
 
8.0%
Uppercase Letter49
 
4.0%
Math Symbol49
 
4.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0507
57.5%
2173
 
19.6%
1132
 
15.0%
948
 
5.4%
76
 
0.7%
45
 
0.6%
55
 
0.6%
33
 
0.3%
82
 
0.2%
61
 
0.1%
Other Punctuation
ValueCountFrequency (%)
:147
100.0%
Dash Punctuation
ValueCountFrequency (%)
-98
100.0%
Uppercase Letter
ValueCountFrequency (%)
T49
100.0%
Math Symbol
ValueCountFrequency (%)
+49
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common1176
96.0%
Latin49
 
4.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0507
43.1%
2173
 
14.7%
:147
 
12.5%
1132
 
11.2%
-98
 
8.3%
+49
 
4.2%
948
 
4.1%
76
 
0.5%
45
 
0.4%
55
 
0.4%
Other values (3)6
 
0.5%
Latin
ValueCountFrequency (%)
T49
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII1225
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0507
41.4%
2173
 
14.1%
:147
 
12.0%
1132
 
10.8%
-98
 
8.0%
T49
 
4.0%
+49
 
4.0%
948
 
3.9%
76
 
0.5%
45
 
0.4%
Other values (4)11
 
0.9%

runtime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct25
Distinct (%)55.6%
Missing4
Missing (%)8.2%
Infinite0
Infinite (%)0.0%
Mean40.02222222
Minimum5
Maximum335
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size520.0 B
2022-09-05T21:45:36.434279image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile7.2
Q117
median25
Q345
95-th percentile108
Maximum335
Range330
Interquartile range (IQR)28

Descriptive statistics

Standard deviation51.32184051
Coefficient of variation (CV)1.282333605
Kurtosis25.55904009
Mean40.02222222
Median Absolute Deviation (MAD)13
Skewness4.638251057
Sum1801
Variance2633.931313
MonotonicityNot monotonic
2022-09-05T21:45:36.527345image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
457
14.3%
303
 
6.1%
153
 
6.1%
203
 
6.1%
603
 
6.1%
232
 
4.1%
192
 
4.1%
162
 
4.1%
72
 
4.1%
252
 
4.1%
Other values (15)16
32.7%
(Missing)4
 
8.2%
ValueCountFrequency (%)
51
 
2.0%
72
4.1%
81
 
2.0%
111
 
2.0%
121
 
2.0%
153
6.1%
162
4.1%
171
 
2.0%
181
 
2.0%
192
4.1%
ValueCountFrequency (%)
3351
 
2.0%
1202
 
4.1%
603
6.1%
591
 
2.0%
511
 
2.0%
501
 
2.0%
461
 
2.0%
457
14.3%
303
6.1%
291
 
2.0%

image
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing49
Missing (%)100.0%
Memory size520.0 B

summary
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct10
Distinct (%)100.0%
Missing39
Missing (%)79.6%
Memory size520.0 B
<p><b>#VacanceAlbumRelease #Thisistheend #(There'sacookie)</b></p>
<p>The Japanese make gains in Malaya, Burma, Hong Kong, Borneo, and the Philippines. The Allies also have trouble in the Atlantic and the Mediterranean, where they are beginning to seriously suffer from a lack of capital ships. The Soviet Red Army is advancing, though, and Stalin takes personal control of planning for the upcoming counteroffensive, while Adolf Hitler takes personal control of the German Army.</p>
<p>Chai, a handsome man, and his friend Om were taking videos secretly and sell the video clips via an "Open Chat" software called "XTH Room". As both encounter a new victim, nothing will be the same.</p>
<p>Yun-hsiang becomes a target of slander, Shen Hua caves under pressure from his father, and Jui-hsin watches Yun-hsiang carry out an act of desperation.</p><p><br /> </p>
<p>Yun-hsiang becomes trapped in a parallel consciousness. Cheng Wen-liang seeks his uncle's aid in preventing Jui-hsin's vengeful plan.</p><p><br /> </p>
Other values (5)

Length

Max length416
Median length178
Mean length207.5
Min length66

Characters and Unicode

Total characters2075
Distinct characters61
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)100.0%

Sample

1st row<p><b>#VacanceAlbumRelease #Thisistheend #(There'sacookie)</b></p>
2nd row<p>The Japanese make gains in Malaya, Burma, Hong Kong, Borneo, and the Philippines. The Allies also have trouble in the Atlantic and the Mediterranean, where they are beginning to seriously suffer from a lack of capital ships. The Soviet Red Army is advancing, though, and Stalin takes personal control of planning for the upcoming counteroffensive, while Adolf Hitler takes personal control of the German Army.</p>
3rd row<p>Chai, a handsome man, and his friend Om were taking videos secretly and sell the video clips via an "Open Chat" software called "XTH Room". As both encounter a new victim, nothing will be the same.</p>
4th row<p>Yun-hsiang becomes a target of slander, Shen Hua caves under pressure from his father, and Jui-hsin watches Yun-hsiang carry out an act of desperation.</p><p><br /> </p>
5th row<p>Yun-hsiang becomes trapped in a parallel consciousness. Cheng Wen-liang seeks his uncle's aid in preventing Jui-hsin's vengeful plan.</p><p><br /> </p>

Common Values

ValueCountFrequency (%)
<p><b>#VacanceAlbumRelease #Thisistheend #(There'sacookie)</b></p>1
 
2.0%
<p>The Japanese make gains in Malaya, Burma, Hong Kong, Borneo, and the Philippines. The Allies also have trouble in the Atlantic and the Mediterranean, where they are beginning to seriously suffer from a lack of capital ships. The Soviet Red Army is advancing, though, and Stalin takes personal control of planning for the upcoming counteroffensive, while Adolf Hitler takes personal control of the German Army.</p>1
 
2.0%
<p>Chai, a handsome man, and his friend Om were taking videos secretly and sell the video clips via an "Open Chat" software called "XTH Room". As both encounter a new victim, nothing will be the same.</p>1
 
2.0%
<p>Yun-hsiang becomes a target of slander, Shen Hua caves under pressure from his father, and Jui-hsin watches Yun-hsiang carry out an act of desperation.</p><p><br /> </p>1
 
2.0%
<p>Yun-hsiang becomes trapped in a parallel consciousness. Cheng Wen-liang seeks his uncle's aid in preventing Jui-hsin's vengeful plan.</p><p><br /> </p>1
 
2.0%
<p>Tregaye Fraser prepares a Sunday feast for her family with love, laughs, stories and great food! She makes her Grandma's Mac and Cheese, Smothered Pork Chops and Collard Greens.</p>1
 
2.0%
<p>Always alone at school, Yamasato was able to live away from reality by writing his fantasy stories in his notebook. In the story, he is the center of the world, and the heroine, by default, is Ai (Hashimoto Ai), the popular girl at the school. But one day when he opened his notebook, he found the rest of the story he had never written... </p>1
 
2.0%
<p><b>"</b><i>It's all out war in Atlas. Our heroes face an impossible problem. Where do they go from here?</i><b>"</b></p>1
 
2.0%
<p>Chef Lovely creates an elegant dinner for close friends. She makes her Roasted Chicken with Pomegranate Glaze, Green Beans Over Lemon Ricotta and Sweet Potato and Gruyere Gratin. Plus, there's an Upside-Down Pear Tart for dessert. You can taste the love!</p>1
 
2.0%
<p>As the group heads for Danibaan, one of them suffers a horrifying injury. With nowhere left to turn, they seek help from a mysterious healer.</p>1
 
2.0%
(Missing)39
79.6%

Length

2022-09-05T21:45:36.624392image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:45:36.742093image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
the19
 
5.8%
and12
 
3.7%
of8
 
2.4%
a8
 
2.4%
in7
 
2.1%
his6
 
1.8%
an5
 
1.5%
for5
 
1.5%
from5
 
1.5%
he4
 
1.2%
Other values (219)249
75.9%

Most occurring characters

ValueCountFrequency (%)
315
15.2%
e205
 
9.9%
a138
 
6.7%
n119
 
5.7%
o110
 
5.3%
s104
 
5.0%
r104
 
5.0%
t102
 
4.9%
i92
 
4.4%
h87
 
4.2%
Other values (51)699
33.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1502
72.4%
Space Separator318
 
15.3%
Uppercase Letter92
 
4.4%
Other Punctuation84
 
4.0%
Math Symbol68
 
3.3%
Dash Punctuation7
 
0.3%
Open Punctuation2
 
0.1%
Close Punctuation2
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e205
13.6%
a138
 
9.2%
n119
 
7.9%
o110
 
7.3%
s104
 
6.9%
r104
 
6.9%
t102
 
6.8%
i92
 
6.1%
h87
 
5.8%
l67
 
4.5%
Other values (14)374
24.9%
Uppercase Letter
ValueCountFrequency (%)
A12
13.0%
C8
 
8.7%
S8
 
8.7%
T8
 
8.7%
G7
 
7.6%
P6
 
6.5%
H5
 
5.4%
R5
 
5.4%
Y5
 
5.4%
O4
 
4.3%
Other values (12)24
26.1%
Other Punctuation
ValueCountFrequency (%)
,27
32.1%
.21
25.0%
/18
21.4%
"6
 
7.1%
'6
 
7.1%
#3
 
3.6%
!2
 
2.4%
?1
 
1.2%
Space Separator
ValueCountFrequency (%)
315
99.1%
 3
 
0.9%
Math Symbol
ValueCountFrequency (%)
>34
50.0%
<34
50.0%
Dash Punctuation
ValueCountFrequency (%)
-7
100.0%
Open Punctuation
ValueCountFrequency (%)
(2
100.0%
Close Punctuation
ValueCountFrequency (%)
)2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1594
76.8%
Common481
 
23.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e205
12.9%
a138
 
8.7%
n119
 
7.5%
o110
 
6.9%
s104
 
6.5%
r104
 
6.5%
t102
 
6.4%
i92
 
5.8%
h87
 
5.5%
l67
 
4.2%
Other values (36)466
29.2%
Common
ValueCountFrequency (%)
315
65.5%
>34
 
7.1%
<34
 
7.1%
,27
 
5.6%
.21
 
4.4%
/18
 
3.7%
-7
 
1.5%
"6
 
1.2%
'6
 
1.2%
 3
 
0.6%
Other values (5)10
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII2072
99.9%
None3
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
315
15.2%
e205
 
9.9%
a138
 
6.7%
n119
 
5.7%
o110
 
5.3%
s104
 
5.0%
r104
 
5.0%
t102
 
4.9%
i92
 
4.4%
h87
 
4.2%
Other values (50)696
33.6%
None
ValueCountFrequency (%)
 3
100.0%

rating.average
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct3
Distinct (%)100.0%
Missing46
Missing (%)93.9%
Memory size520.0 B
5.5
6.5
8.0

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters9
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)100.0%

Sample

1st row5.5
2nd row6.5
3rd row8.0

Common Values

ValueCountFrequency (%)
5.51
 
2.0%
6.51
 
2.0%
8.01
 
2.0%
(Missing)46
93.9%

Length

2022-09-05T21:45:36.877633image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:45:36.958395image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
5.51
33.3%
6.51
33.3%
8.01
33.3%

Most occurring characters

ValueCountFrequency (%)
53
33.3%
.3
33.3%
61
 
11.1%
81
 
11.1%
01
 
11.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number6
66.7%
Other Punctuation3
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
53
50.0%
61
 
16.7%
81
 
16.7%
01
 
16.7%
Other Punctuation
ValueCountFrequency (%)
.3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common9
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
53
33.3%
.3
33.3%
61
 
11.1%
81
 
11.1%
01
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII9
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
53
33.3%
.3
33.3%
61
 
11.1%
81
 
11.1%
01
 
11.1%

_links.self.href
Categorical

HIGH CORRELATION
UNIFORM
UNIQUE

Distinct49
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size520.0 B
https://api.tvmaze.com/episodes/1988862
 
1
https://api.tvmaze.com/episodes/1988596
 
1
https://api.tvmaze.com/episodes/1997520
 
1
https://api.tvmaze.com/episodes/1997521
 
1
https://api.tvmaze.com/episodes/2000064
 
1
Other values (44)
44 

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters1911
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique49 ?
Unique (%)100.0%

Sample

1st rowhttps://api.tvmaze.com/episodes/1988862
2nd rowhttps://api.tvmaze.com/episodes/1989501
3rd rowhttps://api.tvmaze.com/episodes/1989503
4th rowhttps://api.tvmaze.com/episodes/1988697
5th rowhttps://api.tvmaze.com/episodes/2386108

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/19888621
 
2.0%
https://api.tvmaze.com/episodes/19885961
 
2.0%
https://api.tvmaze.com/episodes/19975201
 
2.0%
https://api.tvmaze.com/episodes/19975211
 
2.0%
https://api.tvmaze.com/episodes/20000641
 
2.0%
https://api.tvmaze.com/episodes/20000651
 
2.0%
https://api.tvmaze.com/episodes/20311921
 
2.0%
https://api.tvmaze.com/episodes/20399371
 
2.0%
https://api.tvmaze.com/episodes/21183781
 
2.0%
https://api.tvmaze.com/episodes/21817971
 
2.0%
Other values (39)39
79.6%

Length

2022-09-05T21:45:37.032322image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/19888621
 
2.0%
https://api.tvmaze.com/episodes/19895011
 
2.0%
https://api.tvmaze.com/episodes/19895031
 
2.0%
https://api.tvmaze.com/episodes/19886971
 
2.0%
https://api.tvmaze.com/episodes/23861081
 
2.0%
https://api.tvmaze.com/episodes/21389261
 
2.0%
https://api.tvmaze.com/episodes/19620581
 
2.0%
https://api.tvmaze.com/episodes/19725711
 
2.0%
https://api.tvmaze.com/episodes/19725721
 
2.0%
https://api.tvmaze.com/episodes/20714871
 
2.0%
Other values (39)39
79.6%

Most occurring characters

ValueCountFrequency (%)
/196
 
10.3%
t147
 
7.7%
p147
 
7.7%
s147
 
7.7%
e147
 
7.7%
a98
 
5.1%
i98
 
5.1%
.98
 
5.1%
m98
 
5.1%
o98
 
5.1%
Other values (16)637
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1225
64.1%
Other Punctuation343
 
17.9%
Decimal Number343
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t147
12.0%
p147
12.0%
s147
12.0%
e147
12.0%
a98
8.0%
i98
8.0%
m98
8.0%
o98
8.0%
h49
 
4.0%
d49
 
4.0%
Other values (3)147
12.0%
Decimal Number
ValueCountFrequency (%)
169
20.1%
848
14.0%
247
13.7%
944
12.8%
731
9.0%
028
8.2%
323
 
6.7%
519
 
5.5%
418
 
5.2%
616
 
4.7%
Other Punctuation
ValueCountFrequency (%)
/196
57.1%
.98
28.6%
:49
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin1225
64.1%
Common686
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/196
28.6%
.98
14.3%
169
 
10.1%
:49
 
7.1%
848
 
7.0%
247
 
6.9%
944
 
6.4%
731
 
4.5%
028
 
4.1%
323
 
3.4%
Other values (3)53
 
7.7%
Latin
ValueCountFrequency (%)
t147
12.0%
p147
12.0%
s147
12.0%
e147
12.0%
a98
8.0%
i98
8.0%
m98
8.0%
o98
8.0%
h49
 
4.0%
d49
 
4.0%
Other values (3)147
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII1911
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/196
 
10.3%
t147
 
7.7%
p147
 
7.7%
s147
 
7.7%
e147
 
7.7%
a98
 
5.1%
i98
 
5.1%
.98
 
5.1%
m98
 
5.1%
o98
 
5.1%
Other values (16)637
33.3%

_embedded.show.id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct43
Distinct (%)87.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean46577.95918
Minimum1596
Maximum61755
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size520.0 B
2022-09-05T21:45:37.125305image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1596
5-th percentile10892
Q144057
median51125
Q354762
95-th percentile61123.4
Maximum61755
Range60159
Interquartile range (IQR)10705

Descriptive statistics

Standard deviation14856.04209
Coefficient of variation (CV)0.3189500431
Kurtosis2.503638179
Mean46577.95918
Median Absolute Deviation (MAD)3637
Skewness-1.767047373
Sum2282320
Variance220701986.6
MonotonicityNot monotonic
2022-09-05T21:45:37.231549image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
511252
 
4.1%
479122
 
4.1%
108922
 
4.1%
527432
 
4.1%
547622
 
4.1%
528062
 
4.1%
509391
 
2.0%
608481
 
2.0%
489221
 
2.0%
535641
 
2.0%
Other values (33)33
67.3%
ValueCountFrequency (%)
15961
2.0%
40911
2.0%
108922
4.1%
196671
2.0%
252941
2.0%
306061
2.0%
355511
2.0%
368401
2.0%
402321
2.0%
416481
2.0%
ValueCountFrequency (%)
617551
2.0%
615361
2.0%
613071
2.0%
608481
2.0%
608091
2.0%
588441
2.0%
579561
2.0%
579451
2.0%
566051
2.0%
560671
2.0%

_embedded.show.url
Categorical

HIGH CORRELATION
UNIFORM

Distinct43
Distinct (%)87.8%
Missing0
Missing (%)0.0%
Memory size520.0 B
https://www.tvmaze.com/shows/51125/detention
 
2
https://www.tvmaze.com/shows/47912/the-wolf
 
2
https://www.tvmaze.com/shows/10892/troe-iz-prostokvasino
 
2
https://www.tvmaze.com/shows/52743/the-penalty-zone
 
2
https://www.tvmaze.com/shows/54762/youths-in-the-breeze
 
2
Other values (38)
39 

Length

Max length64
Median length56
Mean length50.51020408
Min length38

Characters and Unicode

Total characters2475
Distinct characters40
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique37 ?
Unique (%)75.5%

Sample

1st rowhttps://www.tvmaze.com/shows/41648/sim-for-you
2nd rowhttps://www.tvmaze.com/shows/10892/troe-iz-prostokvasino
3rd rowhttps://www.tvmaze.com/shows/10892/troe-iz-prostokvasino
4th rowhttps://www.tvmaze.com/shows/35551/soul-land
5th rowhttps://www.tvmaze.com/shows/49206/xian-feng-jian-yu-lu

Common Values

ValueCountFrequency (%)
https://www.tvmaze.com/shows/51125/detention2
 
4.1%
https://www.tvmaze.com/shows/47912/the-wolf2
 
4.1%
https://www.tvmaze.com/shows/10892/troe-iz-prostokvasino2
 
4.1%
https://www.tvmaze.com/shows/52743/the-penalty-zone2
 
4.1%
https://www.tvmaze.com/shows/54762/youths-in-the-breeze2
 
4.1%
https://www.tvmaze.com/shows/52806/ultimate-note2
 
4.1%
https://www.tvmaze.com/shows/50939/rail-romanesque1
 
2.0%
https://www.tvmaze.com/shows/60848/blippi1
 
2.0%
https://www.tvmaze.com/shows/48922/onyx-equinox1
 
2.0%
https://www.tvmaze.com/shows/53564/our-memory1
 
2.0%
Other values (33)33
67.3%

Length

2022-09-05T21:45:37.339612image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.tvmaze.com/shows/51125/detention2
 
4.1%
https://www.tvmaze.com/shows/10892/troe-iz-prostokvasino2
 
4.1%
https://www.tvmaze.com/shows/52743/the-penalty-zone2
 
4.1%
https://www.tvmaze.com/shows/54762/youths-in-the-breeze2
 
4.1%
https://www.tvmaze.com/shows/52806/ultimate-note2
 
4.1%
https://www.tvmaze.com/shows/47912/the-wolf2
 
4.1%
https://www.tvmaze.com/shows/56605/its-okay-to-be-sensitive-20201
 
2.0%
https://www.tvmaze.com/shows/35551/soul-land1
 
2.0%
https://www.tvmaze.com/shows/49206/xian-feng-jian-yu-lu1
 
2.0%
https://www.tvmaze.com/shows/49740/tokyo-joshi-pro-wrestling1
 
2.0%
Other values (33)33
67.3%

Most occurring characters

ValueCountFrequency (%)
/245
 
9.9%
w213
 
8.6%
t203
 
8.2%
s189
 
7.6%
o158
 
6.4%
e132
 
5.3%
h121
 
4.9%
m115
 
4.6%
.98
 
4.0%
a91
 
3.7%
Other values (30)910
36.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1748
70.6%
Other Punctuation392
 
15.8%
Decimal Number247
 
10.0%
Dash Punctuation88
 
3.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w213
12.2%
t203
11.6%
s189
10.8%
o158
 
9.0%
e132
 
7.6%
h121
 
6.9%
m115
 
6.6%
a91
 
5.2%
c61
 
3.5%
p59
 
3.4%
Other values (16)406
23.2%
Decimal Number
ValueCountFrequency (%)
544
17.8%
427
10.9%
626
10.5%
025
10.1%
123
9.3%
223
9.3%
922
8.9%
820
8.1%
319
7.7%
718
7.3%
Other Punctuation
ValueCountFrequency (%)
/245
62.5%
.98
 
25.0%
:49
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-88
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1748
70.6%
Common727
29.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
w213
12.2%
t203
11.6%
s189
10.8%
o158
 
9.0%
e132
 
7.6%
h121
 
6.9%
m115
 
6.6%
a91
 
5.2%
c61
 
3.5%
p59
 
3.4%
Other values (16)406
23.2%
Common
ValueCountFrequency (%)
/245
33.7%
.98
 
13.5%
-88
 
12.1%
:49
 
6.7%
544
 
6.1%
427
 
3.7%
626
 
3.6%
025
 
3.4%
123
 
3.2%
223
 
3.2%
Other values (4)79
 
10.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII2475
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/245
 
9.9%
w213
 
8.6%
t203
 
8.2%
s189
 
7.6%
o158
 
6.4%
e132
 
5.3%
h121
 
4.9%
m115
 
4.6%
.98
 
4.0%
a91
 
3.7%
Other values (30)910
36.8%

_embedded.show.name
Categorical

HIGH CORRELATION
UNIFORM

Distinct43
Distinct (%)87.8%
Missing0
Missing (%)0.0%
Memory size520.0 B
Detention
 
2
The Wolf
 
2
Трое из Простоквашино
 
2
The Penalty Zone
 
2
Youths in the Breeze
 
2
Other values (38)
39 

Length

Max length30
Median length21
Mean length15.73469388
Min length4

Characters and Unicode

Total characters771
Distinct characters82
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique37 ?
Unique (%)75.5%

Sample

1st rowSim for You
2nd rowТрое из Простоквашино
3rd rowТрое из Простоквашино
4th rowSoul Land
5th rowXian Feng Jian Yu Lu

Common Values

ValueCountFrequency (%)
Detention2
 
4.1%
The Wolf2
 
4.1%
Трое из Простоквашино2
 
4.1%
The Penalty Zone2
 
4.1%
Youths in the Breeze2
 
4.1%
Ultimate Note2
 
4.1%
Rail Romanesque1
 
2.0%
Blippi1
 
2.0%
Onyx Equinox1
 
2.0%
Our Memory1
 
2.0%
Other values (33)33
67.3%

Length

2022-09-05T21:45:37.442852image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the8
 
5.8%
in3
 
2.2%
detention2
 
1.5%
ultimate2
 
1.5%
lovely2
 
1.5%
to2
 
1.5%
ufc2
 
1.5%
by2
 
1.5%
fight2
 
1.5%
week2
 
1.5%
Other values (100)110
80.3%

Most occurring characters

ValueCountFrequency (%)
88
 
11.4%
e77
 
10.0%
i44
 
5.7%
o42
 
5.4%
t40
 
5.2%
n37
 
4.8%
a34
 
4.4%
s28
 
3.6%
r28
 
3.6%
l24
 
3.1%
Other values (72)329
42.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter538
69.8%
Uppercase Letter132
 
17.1%
Space Separator88
 
11.4%
Other Punctuation9
 
1.2%
Decimal Number4
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e77
14.3%
i44
 
8.2%
o42
 
7.8%
t40
 
7.4%
n37
 
6.9%
a34
 
6.3%
s28
 
5.2%
r28
 
5.2%
l24
 
4.5%
h19
 
3.5%
Other values (37)165
30.7%
Uppercase Letter
ValueCountFrequency (%)
W14
 
10.6%
T11
 
8.3%
S10
 
7.6%
B9
 
6.8%
D8
 
6.1%
Y7
 
5.3%
R6
 
4.5%
F6
 
4.5%
L6
 
4.5%
U6
 
4.5%
Other values (17)49
37.1%
Other Punctuation
ValueCountFrequency (%)
.3
33.3%
'3
33.3%
?1
 
11.1%
,1
 
11.1%
:1
 
11.1%
Decimal Number
ValueCountFrequency (%)
02
50.0%
22
50.0%
Space Separator
ValueCountFrequency (%)
88
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin616
79.9%
Common101
 
13.1%
Cyrillic54
 
7.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e77
 
12.5%
i44
 
7.1%
o42
 
6.8%
t40
 
6.5%
n37
 
6.0%
a34
 
5.5%
s28
 
4.5%
r28
 
4.5%
l24
 
3.9%
h19
 
3.1%
Other values (41)243
39.4%
Cyrillic
ValueCountFrequency (%)
о12
22.2%
и4
 
7.4%
р4
 
7.4%
е3
 
5.6%
т3
 
5.6%
к2
 
3.7%
м2
 
3.7%
Т2
 
3.7%
з2
 
3.7%
П2
 
3.7%
Other values (13)18
33.3%
Common
ValueCountFrequency (%)
88
87.1%
.3
 
3.0%
'3
 
3.0%
02
 
2.0%
22
 
2.0%
?1
 
1.0%
,1
 
1.0%
:1
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII715
92.7%
Cyrillic54
 
7.0%
None2
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
88
 
12.3%
e77
 
10.8%
i44
 
6.2%
o42
 
5.9%
t40
 
5.6%
n37
 
5.2%
a34
 
4.8%
s28
 
3.9%
r28
 
3.9%
l24
 
3.4%
Other values (47)273
38.2%
Cyrillic
ValueCountFrequency (%)
о12
22.2%
и4
 
7.4%
р4
 
7.4%
е3
 
5.6%
т3
 
5.6%
к2
 
3.7%
м2
 
3.7%
Т2
 
3.7%
з2
 
3.7%
П2
 
3.7%
Other values (13)18
33.3%
None
ValueCountFrequency (%)
ø1
50.0%
å1
50.0%

_embedded.show.type
Categorical

HIGH CORRELATION

Distinct8
Distinct (%)16.3%
Missing0
Missing (%)0.0%
Memory size520.0 B
Scripted
23 
Animation
Documentary
Sports
Reality
Other values (3)

Length

Max length11
Median length9
Mean length8.326530612
Min length6

Characters and Unicode

Total characters408
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)2.0%

Sample

1st rowReality
2nd rowAnimation
3rd rowAnimation
4th rowAnimation
5th rowAnimation

Common Values

ValueCountFrequency (%)
Scripted23
46.9%
Animation8
 
16.3%
Documentary5
 
10.2%
Sports4
 
8.2%
Reality3
 
6.1%
Talk Show3
 
6.1%
Game Show2
 
4.1%
Variety1
 
2.0%

Length

2022-09-05T21:45:37.533351image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:45:37.627399image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
scripted23
42.6%
animation8
 
14.8%
documentary5
 
9.3%
show5
 
9.3%
sports4
 
7.4%
reality3
 
5.6%
talk3
 
5.6%
game2
 
3.7%
variety1
 
1.9%

Most occurring characters

ValueCountFrequency (%)
t44
10.8%
i43
10.5%
e34
 
8.3%
r33
 
8.1%
S32
 
7.8%
c28
 
6.9%
p27
 
6.6%
d23
 
5.6%
a22
 
5.4%
o22
 
5.4%
Other values (16)100
24.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter349
85.5%
Uppercase Letter54
 
13.2%
Space Separator5
 
1.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t44
12.6%
i43
12.3%
e34
9.7%
r33
9.5%
c28
8.0%
p27
7.7%
d23
6.6%
a22
6.3%
o22
6.3%
n21
6.0%
Other values (8)52
14.9%
Uppercase Letter
ValueCountFrequency (%)
S32
59.3%
A8
 
14.8%
D5
 
9.3%
T3
 
5.6%
R3
 
5.6%
G2
 
3.7%
V1
 
1.9%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin403
98.8%
Common5
 
1.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
t44
10.9%
i43
10.7%
e34
 
8.4%
r33
 
8.2%
S32
 
7.9%
c28
 
6.9%
p27
 
6.7%
d23
 
5.7%
a22
 
5.5%
o22
 
5.5%
Other values (15)95
23.6%
Common
ValueCountFrequency (%)
5
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII408
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t44
10.8%
i43
10.5%
e34
 
8.3%
r33
 
8.1%
S32
 
7.8%
c28
 
6.9%
p27
 
6.6%
d23
 
5.6%
a22
 
5.4%
o22
 
5.4%
Other values (16)100
24.5%

_embedded.show.language
Categorical

HIGH CORRELATION

Distinct11
Distinct (%)22.4%
Missing0
Missing (%)0.0%
Memory size520.0 B
Chinese
14 
English
14 
Norwegian
Russian
Japanese
Other values (6)

Length

Max length9
Median length7
Mean length7.102040816
Min length4

Characters and Unicode

Total characters348
Distinct characters27
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)10.2%

Sample

1st rowKorean
2nd rowRussian
3rd rowRussian
4th rowChinese
5th rowChinese

Common Values

ValueCountFrequency (%)
Chinese14
28.6%
English14
28.6%
Norwegian5
 
10.2%
Russian4
 
8.2%
Japanese4
 
8.2%
Korean3
 
6.1%
Dutch1
 
2.0%
Thai1
 
2.0%
Tagalog1
 
2.0%
Panjabi1
 
2.0%

Length

2022-09-05T21:45:37.715626image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
chinese14
28.6%
english14
28.6%
norwegian5
 
10.2%
russian4
 
8.2%
japanese4
 
8.2%
korean3
 
6.1%
dutch1
 
2.0%
thai1
 
2.0%
tagalog1
 
2.0%
panjabi1
 
2.0%

Most occurring characters

ValueCountFrequency (%)
n45
12.9%
e44
12.6%
i40
11.5%
s40
11.5%
h30
8.6%
a26
7.5%
g21
 
6.0%
l15
 
4.3%
C14
 
4.0%
E14
 
4.0%
Other values (17)59
17.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter299
85.9%
Uppercase Letter49
 
14.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n45
15.1%
e44
14.7%
i40
13.4%
s40
13.4%
h30
10.0%
a26
8.7%
g21
7.0%
l15
 
5.0%
o9
 
3.0%
r9
 
3.0%
Other values (7)20
6.7%
Uppercase Letter
ValueCountFrequency (%)
C14
28.6%
E14
28.6%
N5
 
10.2%
R4
 
8.2%
J4
 
8.2%
K3
 
6.1%
T2
 
4.1%
D1
 
2.0%
P1
 
2.0%
A1
 
2.0%

Most occurring scripts

ValueCountFrequency (%)
Latin348
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
n45
12.9%
e44
12.6%
i40
11.5%
s40
11.5%
h30
8.6%
a26
7.5%
g21
 
6.0%
l15
 
4.3%
C14
 
4.0%
E14
 
4.0%
Other values (17)59
17.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII348
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n45
12.9%
e44
12.6%
i40
11.5%
s40
11.5%
h30
8.6%
a26
7.5%
g21
 
6.0%
l15
 
4.3%
C14
 
4.0%
E14
 
4.0%
Other values (17)59
17.0%

_embedded.show.genres
Unsupported

REJECTED
UNSUPPORTED

Missing0
Missing (%)0.0%
Memory size520.0 B

_embedded.show.status
Categorical

HIGH CORRELATION

Distinct3
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size520.0 B
Running
25 
Ended
19 
To Be Determined

Length

Max length16
Median length7
Mean length7.142857143
Min length5

Characters and Unicode

Total characters350
Distinct characters16
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowRunning
2nd rowRunning
3rd rowRunning
4th rowRunning
5th rowRunning

Common Values

ValueCountFrequency (%)
Running25
51.0%
Ended19
38.8%
To Be Determined5
 
10.2%

Length

2022-09-05T21:45:37.802175image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:45:37.882053image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
running25
42.4%
ended19
32.2%
to5
 
8.5%
be5
 
8.5%
determined5
 
8.5%

Most occurring characters

ValueCountFrequency (%)
n99
28.3%
d43
12.3%
e39
 
11.1%
i30
 
8.6%
R25
 
7.1%
u25
 
7.1%
g25
 
7.1%
E19
 
5.4%
10
 
2.9%
T5
 
1.4%
Other values (6)30
 
8.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter281
80.3%
Uppercase Letter59
 
16.9%
Space Separator10
 
2.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n99
35.2%
d43
15.3%
e39
 
13.9%
i30
 
10.7%
u25
 
8.9%
g25
 
8.9%
o5
 
1.8%
t5
 
1.8%
r5
 
1.8%
m5
 
1.8%
Uppercase Letter
ValueCountFrequency (%)
R25
42.4%
E19
32.2%
T5
 
8.5%
B5
 
8.5%
D5
 
8.5%
Space Separator
ValueCountFrequency (%)
10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin340
97.1%
Common10
 
2.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
n99
29.1%
d43
12.6%
e39
 
11.5%
i30
 
8.8%
R25
 
7.4%
u25
 
7.4%
g25
 
7.4%
E19
 
5.6%
T5
 
1.5%
o5
 
1.5%
Other values (5)25
 
7.4%
Common
ValueCountFrequency (%)
10
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII350
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n99
28.3%
d43
12.3%
e39
 
11.1%
i30
 
8.6%
R25
 
7.1%
u25
 
7.1%
g25
 
7.1%
E19
 
5.4%
10
 
2.9%
T5
 
1.4%
Other values (6)30
 
8.6%

_embedded.show.runtime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct14
Distinct (%)38.9%
Missing13
Missing (%)26.5%
Infinite0
Infinite (%)0.0%
Mean34.30555556
Minimum5
Maximum120
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size520.0 B
2022-09-05T21:45:37.948111image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile7
Q115
median25
Q345
95-th percentile120
Maximum120
Range115
Interquartile range (IQR)30

Descriptive statistics

Standard deviation30.21335508
Coefficient of variation (CV)0.8807131846
Kurtosis3.530252824
Mean34.30555556
Median Absolute Deviation (MAD)15.5
Skewness1.919911864
Sum1235
Variance912.8468254
MonotonicityNot monotonic
2022-09-05T21:45:38.038156image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
457
14.3%
74
 
8.2%
254
 
8.2%
304
 
8.2%
203
 
6.1%
1203
 
6.1%
153
 
6.1%
602
 
4.1%
161
 
2.0%
81
 
2.0%
Other values (4)4
 
8.2%
(Missing)13
26.5%
ValueCountFrequency (%)
51
 
2.0%
74
8.2%
81
 
2.0%
111
 
2.0%
153
6.1%
161
 
2.0%
203
6.1%
231
 
2.0%
241
 
2.0%
254
8.2%
ValueCountFrequency (%)
1203
6.1%
602
 
4.1%
457
14.3%
304
8.2%
254
8.2%
241
 
2.0%
231
 
2.0%
203
6.1%
161
 
2.0%
153
6.1%

_embedded.show.averageRuntime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct27
Distinct (%)61.4%
Missing5
Missing (%)10.2%
Infinite0
Infinite (%)0.0%
Mean35.93181818
Minimum5
Maximum194
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size520.0 B
2022-09-05T21:45:38.126574image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile7
Q114.75
median25
Q345
95-th percentile113.1
Maximum194
Range189
Interquartile range (IQR)30.25

Descriptive statistics

Standard deviation35.20134625
Coefficient of variation (CV)0.9796706105
Kurtosis9.548151058
Mean35.93181818
Median Absolute Deviation (MAD)14
Skewness2.778209342
Sum1581
Variance1239.134778
MonotonicityNot monotonic
2022-09-05T21:45:38.229195image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
456
 
12.2%
303
 
6.1%
73
 
6.1%
113
 
6.1%
232
 
4.1%
202
 
4.1%
1202
 
4.1%
252
 
4.1%
512
 
4.1%
142
 
4.1%
Other values (17)17
34.7%
(Missing)5
 
10.2%
ValueCountFrequency (%)
51
 
2.0%
73
6.1%
91
 
2.0%
113
6.1%
131
 
2.0%
142
4.1%
151
 
2.0%
161
 
2.0%
171
 
2.0%
181
 
2.0%
ValueCountFrequency (%)
1941
 
2.0%
1202
 
4.1%
741
 
2.0%
601
 
2.0%
561
 
2.0%
512
 
4.1%
456
12.2%
431
 
2.0%
391
 
2.0%
303
6.1%

_embedded.show.premiered
Categorical

HIGH CORRELATION
UNIFORM

Distinct40
Distinct (%)81.6%
Missing0
Missing (%)0.0%
Memory size520.0 B
2020-12-05
 
3
2020-12-10
 
2
1978-06-10
 
2
2020-11-14
 
2
2020-11-19
 
2
Other values (35)
38 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters490
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique32 ?
Unique (%)65.3%

Sample

1st row2019-03-25
2nd row1978-06-10
3rd row1978-06-10
4th row2018-01-13
5th row2020-07-11

Common Values

ValueCountFrequency (%)
2020-12-053
 
6.1%
2020-12-102
 
4.1%
1978-06-102
 
4.1%
2020-11-142
 
4.1%
2020-11-192
 
4.1%
2020-12-132
 
4.1%
2020-10-032
 
4.1%
2020-12-162
 
4.1%
2014-09-231
 
2.0%
2020-10-201
 
2.0%
Other values (30)30
61.2%

Length

2022-09-05T21:45:38.320109image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-12-053
 
6.1%
1978-06-102
 
4.1%
2020-11-142
 
4.1%
2020-11-192
 
4.1%
2020-12-132
 
4.1%
2020-10-032
 
4.1%
2020-12-162
 
4.1%
2020-12-102
 
4.1%
2020-09-191
 
2.0%
2020-07-111
 
2.0%
Other values (30)30
61.2%

Most occurring characters

ValueCountFrequency (%)
0124
25.3%
2101
20.6%
-98
20.0%
191
18.6%
920
 
4.1%
312
 
2.4%
811
 
2.2%
710
 
2.0%
610
 
2.0%
59
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number392
80.0%
Dash Punctuation98
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0124
31.6%
2101
25.8%
191
23.2%
920
 
5.1%
312
 
3.1%
811
 
2.8%
710
 
2.6%
610
 
2.6%
59
 
2.3%
44
 
1.0%
Dash Punctuation
ValueCountFrequency (%)
-98
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common490
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0124
25.3%
2101
20.6%
-98
20.0%
191
18.6%
920
 
4.1%
312
 
2.4%
811
 
2.2%
710
 
2.0%
610
 
2.0%
59
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII490
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0124
25.3%
2101
20.6%
-98
20.0%
191
18.6%
920
 
4.1%
312
 
2.4%
811
 
2.2%
710
 
2.0%
610
 
2.0%
59
 
1.8%

_embedded.show.ended
Categorical

HIGH CORRELATION
MISSING

Distinct10
Distinct (%)52.6%
Missing30
Missing (%)61.2%
Memory size520.0 B
2021-01-02
2020-12-19
2021-01-09
2021-01-04
2020-12-22
Other values (5)

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters190
Distinct characters9
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)21.1%

Sample

1st row2021-01-04
2nd row2021-01-04
3rd row2020-12-22
4th row2020-12-22
5th row2020-12-24

Common Values

ValueCountFrequency (%)
2021-01-023
 
6.1%
2020-12-193
 
6.1%
2021-01-093
 
6.1%
2021-01-042
 
4.1%
2020-12-222
 
4.1%
2020-12-262
 
4.1%
2020-12-241
 
2.0%
2021-03-011
 
2.0%
2021-01-231
 
2.0%
2021-08-211
 
2.0%
(Missing)30
61.2%

Length

2022-09-05T21:45:38.399858image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:45:38.507830image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
2021-01-023
15.8%
2020-12-193
15.8%
2021-01-093
15.8%
2021-01-042
10.5%
2020-12-222
10.5%
2020-12-262
10.5%
2020-12-241
 
5.3%
2021-03-011
 
5.3%
2021-01-231
 
5.3%
2021-08-211
 
5.3%

Most occurring characters

ValueCountFrequency (%)
258
30.5%
047
24.7%
-38
20.0%
133
17.4%
96
 
3.2%
43
 
1.6%
62
 
1.1%
32
 
1.1%
81
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number152
80.0%
Dash Punctuation38
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
258
38.2%
047
30.9%
133
21.7%
96
 
3.9%
43
 
2.0%
62
 
1.3%
32
 
1.3%
81
 
0.7%
Dash Punctuation
ValueCountFrequency (%)
-38
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common190
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
258
30.5%
047
24.7%
-38
20.0%
133
17.4%
96
 
3.2%
43
 
1.6%
62
 
1.1%
32
 
1.1%
81
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII190
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
258
30.5%
047
24.7%
-38
20.0%
133
17.4%
96
 
3.2%
43
 
1.6%
62
 
1.1%
32
 
1.1%
81
 
0.5%

_embedded.show.officialSite
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct39
Distinct (%)86.7%
Missing4
Missing (%)8.2%
Memory size520.0 B
https://www.netflix.com/title/81329144
 
2
https://www.iqiyi.com/lib/m_213579814.html
 
2
https://okko.tv/serial/prostokvashino
 
2
https://www.iqiyi.com/a_19rrhllpip.html
 
2
https://v.youku.com/v_show/id_XNDk4OTUxMzg1Mg==.html?spm=a2hbt.13141534.0.13141534&s=6eefbfbd4befbfbd32ef
 
2
Other values (34)
35 

Length

Max length105
Median length70
Mean length49.26666667
Min length19

Characters and Unicode

Total characters2217
Distinct characters71
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33 ?
Unique (%)73.3%

Sample

1st rowhttps://www.vlive.tv/video/121637
2nd rowhttps://okko.tv/serial/prostokvashino
3rd rowhttps://okko.tv/serial/prostokvashino
4th rowhttps://v.qq.com/detail/m/m441e3rjq9kwpsc.html
5th rowhttps://v.qq.com/detail/m/mzc00200hc38s5x.html

Common Values

ValueCountFrequency (%)
https://www.netflix.com/title/813291442
 
4.1%
https://www.iqiyi.com/lib/m_213579814.html2
 
4.1%
https://okko.tv/serial/prostokvashino2
 
4.1%
https://www.iqiyi.com/a_19rrhllpip.html2
 
4.1%
https://v.youku.com/v_show/id_XNDk4OTUxMzg1Mg==.html?spm=a2hbt.13141534.0.13141534&s=6eefbfbd4befbfbd32ef2
 
4.1%
https://www.iqiyi.com/a_nvzsmw0tgx.html2
 
4.1%
https://railromanesque.jp1
 
2.0%
https://www.ufc.tv/page/fightpass1
 
2.0%
http://www.wwe.com/shows/wwe-talking-smack1
 
2.0%
https://roosterteeth.com/series/rwby1
 
2.0%
Other values (29)29
59.2%
(Missing)4
 
8.2%

Length

2022-09-05T21:45:38.614107image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.netflix.com/title/813291442
 
4.4%
https://okko.tv/serial/prostokvashino2
 
4.4%
https://www.iqiyi.com/a_19rrhllpip.html2
 
4.4%
https://v.youku.com/v_show/id_xndk4otuxmzg1mg==.html?spm=a2hbt.13141534.0.13141534&s=6eefbfbd4befbfbd32ef2
 
4.4%
https://www.iqiyi.com/a_nvzsmw0tgx.html2
 
4.4%
https://www.iqiyi.com/lib/m_213579814.html2
 
4.4%
https://tv.kakao.com/channel/3658620/cliplink/415324903?metaobjecttype=channel1
 
2.2%
https://v.qq.com/detail/m/m441e3rjq9kwpsc.html1
 
2.2%
https://v.qq.com/detail/m/mzc00200hc38s5x.html1
 
2.2%
https://www.ddtpro.com1
 
2.2%
Other values (29)29
64.4%

Most occurring characters

ValueCountFrequency (%)
t180
 
8.1%
/177
 
8.0%
s118
 
5.3%
w105
 
4.7%
.102
 
4.6%
e96
 
4.3%
o96
 
4.3%
h91
 
4.1%
i86
 
3.9%
p83
 
3.7%
Other values (61)1083
48.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1498
67.6%
Other Punctuation345
 
15.6%
Decimal Number192
 
8.7%
Uppercase Letter127
 
5.7%
Dash Punctuation22
 
1.0%
Math Symbol19
 
0.9%
Connector Punctuation14
 
0.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t180
 
12.0%
s118
 
7.9%
w105
 
7.0%
e96
 
6.4%
o96
 
6.4%
h91
 
6.1%
i86
 
5.7%
p83
 
5.5%
l69
 
4.6%
m64
 
4.3%
Other values (16)510
34.0%
Uppercase Letter
ValueCountFrequency (%)
P12
 
9.4%
A8
 
6.3%
M8
 
6.3%
L8
 
6.3%
T8
 
6.3%
Y7
 
5.5%
N7
 
5.5%
B6
 
4.7%
W6
 
4.7%
O6
 
4.7%
Other values (16)51
40.2%
Decimal Number
ValueCountFrequency (%)
432
16.7%
131
16.1%
325
13.0%
224
12.5%
020
10.4%
518
9.4%
612
 
6.2%
911
 
5.7%
811
 
5.7%
78
 
4.2%
Other Punctuation
ValueCountFrequency (%)
/177
51.3%
.102
29.6%
:45
 
13.0%
?9
 
2.6%
%6
 
1.7%
&6
 
1.7%
Dash Punctuation
ValueCountFrequency (%)
-22
100.0%
Math Symbol
ValueCountFrequency (%)
=19
100.0%
Connector Punctuation
ValueCountFrequency (%)
_14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1625
73.3%
Common592
 
26.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
t180
 
11.1%
s118
 
7.3%
w105
 
6.5%
e96
 
5.9%
o96
 
5.9%
h91
 
5.6%
i86
 
5.3%
p83
 
5.1%
l69
 
4.2%
m64
 
3.9%
Other values (42)637
39.2%
Common
ValueCountFrequency (%)
/177
29.9%
.102
17.2%
:45
 
7.6%
432
 
5.4%
131
 
5.2%
325
 
4.2%
224
 
4.1%
-22
 
3.7%
020
 
3.4%
=19
 
3.2%
Other values (9)95
16.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII2217
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t180
 
8.1%
/177
 
8.0%
s118
 
5.3%
w105
 
4.7%
.102
 
4.6%
e96
 
4.3%
o96
 
4.3%
h91
 
4.1%
i86
 
3.9%
p83
 
3.7%
Other values (61)1083
48.8%

_embedded.show.schedule.time
Categorical

HIGH CORRELATION

Distinct11
Distinct (%)22.4%
Missing0
Missing (%)0.0%
Memory size520.0 B
36 
12:00
 
3
10:00
 
2
11:00
 
1
06:00
 
1
Other values (6)

Length

Max length5
Median length0
Mean length1.326530612
Min length0

Characters and Unicode

Total characters65
Distinct characters8
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)16.3%

Sample

1st row
2nd row12:00
3rd row12:00
4th row10:00
5th row10:00

Common Values

ValueCountFrequency (%)
36
73.5%
12:003
 
6.1%
10:002
 
4.1%
11:001
 
2.0%
06:001
 
2.0%
17:001
 
2.0%
18:001
 
2.0%
00:001
 
2.0%
00:151
 
2.0%
16:001
 
2.0%

Length

2022-09-05T21:45:38.706341image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
12:003
23.1%
10:002
15.4%
11:001
 
7.7%
06:001
 
7.7%
17:001
 
7.7%
18:001
 
7.7%
00:001
 
7.7%
00:151
 
7.7%
16:001
 
7.7%
22:001
 
7.7%

Most occurring characters

ValueCountFrequency (%)
031
47.7%
:13
20.0%
111
 
16.9%
25
 
7.7%
62
 
3.1%
71
 
1.5%
81
 
1.5%
51
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number52
80.0%
Other Punctuation13
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
031
59.6%
111
 
21.2%
25
 
9.6%
62
 
3.8%
71
 
1.9%
81
 
1.9%
51
 
1.9%
Other Punctuation
ValueCountFrequency (%)
:13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common65
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
031
47.7%
:13
20.0%
111
 
16.9%
25
 
7.7%
62
 
3.1%
71
 
1.5%
81
 
1.5%
51
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII65
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
031
47.7%
:13
20.0%
111
 
16.9%
25
 
7.7%
62
 
3.1%
71
 
1.5%
81
 
1.5%
51
 
1.5%

_embedded.show.schedule.days
Unsupported

REJECTED
UNSUPPORTED

Missing0
Missing (%)0.0%
Memory size520.0 B

_embedded.show.rating.average
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct4
Distinct (%)57.1%
Missing42
Missing (%)85.7%
Memory size520.0 B
7.7
7.5
7.3
5.0

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters21
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)28.6%

Sample

1st row7.5
2nd row7.5
3rd row7.7
4th row7.3
5th row7.7

Common Values

ValueCountFrequency (%)
7.73
 
6.1%
7.52
 
4.1%
7.31
 
2.0%
5.01
 
2.0%
(Missing)42
85.7%

Length

2022-09-05T21:45:38.787942image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:45:38.877686image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
7.73
42.9%
7.52
28.6%
7.31
 
14.3%
5.01
 
14.3%

Most occurring characters

ValueCountFrequency (%)
79
42.9%
.7
33.3%
53
 
14.3%
31
 
4.8%
01
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number14
66.7%
Other Punctuation7
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
79
64.3%
53
 
21.4%
31
 
7.1%
01
 
7.1%
Other Punctuation
ValueCountFrequency (%)
.7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common21
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
79
42.9%
.7
33.3%
53
 
14.3%
31
 
4.8%
01
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII21
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
79
42.9%
.7
33.3%
53
 
14.3%
31
 
4.8%
01
 
4.8%

_embedded.show.weight
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct34
Distinct (%)69.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38.57142857
Minimum1
Maximum95
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size520.0 B
2022-09-05T21:45:38.963956image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.4
Q120
median33
Q352
95-th percentile90.2
Maximum95
Range94
Interquartile range (IQR)32

Descriptive statistics

Standard deviation26.88401012
Coefficient of variation (CV)0.6969928549
Kurtosis-0.5004637981
Mean38.57142857
Median Absolute Deviation (MAD)14
Skewness0.5802272668
Sum1890
Variance722.75
MonotonicityNot monotonic
2022-09-05T21:45:39.063396image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
303
 
6.1%
273
 
6.1%
13
 
6.1%
452
 
4.1%
892
 
4.1%
82
 
4.1%
212
 
4.1%
292
 
4.1%
382
 
4.1%
442
 
4.1%
Other values (24)26
53.1%
ValueCountFrequency (%)
13
6.1%
21
 
2.0%
41
 
2.0%
71
 
2.0%
82
4.1%
91
 
2.0%
131
 
2.0%
192
4.1%
201
 
2.0%
212
4.1%
ValueCountFrequency (%)
951
2.0%
921
2.0%
911
2.0%
892
4.1%
791
2.0%
741
2.0%
731
2.0%
651
2.0%
631
2.0%
621
2.0%

_embedded.show.network
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing49
Missing (%)100.0%
Memory size520.0 B

_embedded.show.webChannel.id
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct26
Distinct (%)54.2%
Missing1
Missing (%)2.0%
Infinite0
Infinite (%)0.0%
Mean153.2708333
Minimum1
Maximum533
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size520.0 B
2022-09-05T21:45:39.150014image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile16.75
Q121
median104
Q3272.25
95-th percentile397.85
Maximum533
Range532
Interquartile range (IQR)251.25

Descriptive statistics

Standard deviation148.6112649
Coefficient of variation (CV)0.9695991188
Kurtosis-0.6029401323
Mean153.2708333
Median Absolute Deviation (MAD)83
Skewness0.8132868344
Sum7357
Variance22085.30807
MonotonicityNot monotonic
2022-09-05T21:45:39.248460image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
2110
20.4%
674
 
8.2%
1184
 
8.2%
2383
 
6.1%
1042
 
4.1%
202
 
4.1%
12
 
4.1%
3662
 
4.1%
3272
 
4.1%
1221
 
2.0%
Other values (16)16
32.7%
ValueCountFrequency (%)
12
 
4.1%
151
 
2.0%
202
 
4.1%
2110
20.4%
301
 
2.0%
321
 
2.0%
451
 
2.0%
511
 
2.0%
674
 
8.2%
1042
 
4.1%
ValueCountFrequency (%)
5331
2.0%
4521
2.0%
4081
2.0%
3791
2.0%
3671
2.0%
3662
4.1%
3421
2.0%
3272
4.1%
3211
2.0%
2941
2.0%

_embedded.show.webChannel.name
Categorical

HIGH CORRELATION
MISSING

Distinct26
Distinct (%)54.2%
Missing1
Missing (%)2.0%
Memory size520.0 B
YouTube
10 
iQIYI
Youku
NRK TV
Tencent QQ
 
2
Other values (21)
25 

Length

Max length14
Median length12
Mean length7.5625
Min length4

Characters and Unicode

Total characters363
Distinct characters47
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)35.4%

Sample

1st rowV LIVE
2nd rowOkko
3rd rowOkko
4th rowTencent QQ
5th rowTencent QQ

Common Values

ValueCountFrequency (%)
YouTube10
20.4%
iQIYI4
 
8.2%
Youku4
 
8.2%
NRK TV3
 
6.1%
Tencent QQ2
 
4.1%
Crunchyroll2
 
4.1%
Netflix2
 
4.1%
Okko2
 
4.1%
TV 2 Play2
 
4.1%
V LIVE1
 
2.0%
Other values (16)16
32.7%

Length

2022-09-05T21:45:39.343125image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
youtube10
 
15.6%
tv6
 
9.4%
youku4
 
6.2%
iqiyi4
 
6.2%
nrk3
 
4.7%
netflix2
 
3.1%
22
 
3.1%
okko2
 
3.1%
play2
 
3.1%
crunchyroll2
 
3.1%
Other values (25)27
42.2%

Most occurring characters

ValueCountFrequency (%)
u32
 
8.8%
e28
 
7.7%
o27
 
7.4%
T23
 
6.3%
Y18
 
5.0%
16
 
4.4%
i16
 
4.4%
l13
 
3.6%
r13
 
3.6%
b12
 
3.3%
Other values (37)165
45.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter222
61.2%
Uppercase Letter120
33.1%
Space Separator16
 
4.4%
Math Symbol2
 
0.6%
Decimal Number2
 
0.6%
Other Punctuation1
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
u32
14.4%
e28
12.6%
o27
12.2%
i16
 
7.2%
l13
 
5.9%
r13
 
5.9%
b12
 
5.4%
a11
 
5.0%
t11
 
5.0%
k11
 
5.0%
Other values (13)48
21.6%
Uppercase Letter
ValueCountFrequency (%)
T23
19.2%
Y18
15.0%
V10
 
8.3%
I9
 
7.5%
N8
 
6.7%
Q8
 
6.7%
P5
 
4.2%
C5
 
4.2%
S4
 
3.3%
E4
 
3.3%
Other values (10)26
21.7%
Space Separator
ValueCountFrequency (%)
16
100.0%
Math Symbol
ValueCountFrequency (%)
+2
100.0%
Decimal Number
ValueCountFrequency (%)
22
100.0%
Other Punctuation
ValueCountFrequency (%)
.1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin342
94.2%
Common21
 
5.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
u32
 
9.4%
e28
 
8.2%
o27
 
7.9%
T23
 
6.7%
Y18
 
5.3%
i16
 
4.7%
l13
 
3.8%
r13
 
3.8%
b12
 
3.5%
a11
 
3.2%
Other values (33)149
43.6%
Common
ValueCountFrequency (%)
16
76.2%
+2
 
9.5%
22
 
9.5%
.1
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII363
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
u32
 
8.8%
e28
 
7.7%
o27
 
7.4%
T23
 
6.3%
Y18
 
5.0%
16
 
4.4%
i16
 
4.4%
l13
 
3.6%
r13
 
3.6%
b12
 
3.3%
Other values (37)165
45.5%

_embedded.show.webChannel.country.name
Categorical

HIGH CORRELATION
MISSING

Distinct7
Distinct (%)26.9%
Missing23
Missing (%)46.9%
Memory size520.0 B
China
Norway
United States
Korea, Republic of
Japan
Other values (2)

Length

Max length18
Median length13
Mean length9.423076923
Min length5

Characters and Unicode

Total characters245
Distinct characters30
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)3.8%

Sample

1st rowKorea, Republic of
2nd rowRussian Federation
3rd rowRussian Federation
4th rowChina
5th rowChina

Common Values

ValueCountFrequency (%)
China7
 
14.3%
Norway5
 
10.2%
United States5
 
10.2%
Korea, Republic of3
 
6.1%
Japan3
 
6.1%
Russian Federation2
 
4.1%
Kazakhstan1
 
2.0%
(Missing)23
46.9%

Length

2022-09-05T21:45:39.436026image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:45:39.533498image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
china7
17.9%
norway5
12.8%
united5
12.8%
states5
12.8%
korea3
7.7%
republic3
7.7%
of3
7.7%
japan3
7.7%
russian2
 
5.1%
federation2
 
5.1%

Most occurring characters

ValueCountFrequency (%)
a33
13.5%
n20
 
8.2%
e20
 
8.2%
i19
 
7.8%
t18
 
7.3%
o13
 
5.3%
13
 
5.3%
r10
 
4.1%
s10
 
4.1%
h8
 
3.3%
Other values (20)81
33.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter193
78.8%
Uppercase Letter36
 
14.7%
Space Separator13
 
5.3%
Other Punctuation3
 
1.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a33
17.1%
n20
10.4%
e20
10.4%
i19
9.8%
t18
9.3%
o13
 
6.7%
r10
 
5.2%
s10
 
5.2%
h8
 
4.1%
d7
 
3.6%
Other values (10)35
18.1%
Uppercase Letter
ValueCountFrequency (%)
C7
19.4%
R5
13.9%
S5
13.9%
U5
13.9%
N5
13.9%
K4
11.1%
J3
8.3%
F2
 
5.6%
Space Separator
ValueCountFrequency (%)
13
100.0%
Other Punctuation
ValueCountFrequency (%)
,3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin229
93.5%
Common16
 
6.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
a33
14.4%
n20
 
8.7%
e20
 
8.7%
i19
 
8.3%
t18
 
7.9%
o13
 
5.7%
r10
 
4.4%
s10
 
4.4%
h8
 
3.5%
C7
 
3.1%
Other values (18)71
31.0%
Common
ValueCountFrequency (%)
13
81.2%
,3
 
18.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII245
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a33
13.5%
n20
 
8.2%
e20
 
8.2%
i19
 
7.8%
t18
 
7.3%
o13
 
5.3%
13
 
5.3%
r10
 
4.1%
s10
 
4.1%
h8
 
3.3%
Other values (20)81
33.1%

_embedded.show.webChannel.country.code
Categorical

HIGH CORRELATION
MISSING

Distinct7
Distinct (%)26.9%
Missing23
Missing (%)46.9%
Memory size520.0 B
CN
NO
US
KR
JP
Other values (2)

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters52
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)3.8%

Sample

1st rowKR
2nd rowRU
3rd rowRU
4th rowCN
5th rowCN

Common Values

ValueCountFrequency (%)
CN7
 
14.3%
NO5
 
10.2%
US5
 
10.2%
KR3
 
6.1%
JP3
 
6.1%
RU2
 
4.1%
KZ1
 
2.0%
(Missing)23
46.9%

Length

2022-09-05T21:45:39.618949image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:45:39.709583image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
cn7
26.9%
no5
19.2%
us5
19.2%
kr3
11.5%
jp3
11.5%
ru2
 
7.7%
kz1
 
3.8%

Most occurring characters

ValueCountFrequency (%)
N12
23.1%
C7
13.5%
U7
13.5%
O5
9.6%
S5
9.6%
R5
9.6%
K4
 
7.7%
J3
 
5.8%
P3
 
5.8%
Z1
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter52
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N12
23.1%
C7
13.5%
U7
13.5%
O5
9.6%
S5
9.6%
R5
9.6%
K4
 
7.7%
J3
 
5.8%
P3
 
5.8%
Z1
 
1.9%

Most occurring scripts

ValueCountFrequency (%)
Latin52
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N12
23.1%
C7
13.5%
U7
13.5%
O5
9.6%
S5
9.6%
R5
9.6%
K4
 
7.7%
J3
 
5.8%
P3
 
5.8%
Z1
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII52
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N12
23.1%
C7
13.5%
U7
13.5%
O5
9.6%
S5
9.6%
R5
9.6%
K4
 
7.7%
J3
 
5.8%
P3
 
5.8%
Z1
 
1.9%

_embedded.show.webChannel.country.timezone
Categorical

HIGH CORRELATION
MISSING

Distinct7
Distinct (%)26.9%
Missing23
Missing (%)46.9%
Memory size520.0 B
Asia/Shanghai
Europe/Oslo
America/New_York
Asia/Seoul
Asia/Tokyo
Other values (2)

Length

Max length16
Median length13.5
Mean length12.61538462
Min length10

Characters and Unicode

Total characters328
Distinct characters31
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)3.8%

Sample

1st rowAsia/Seoul
2nd rowAsia/Kamchatka
3rd rowAsia/Kamchatka
4th rowAsia/Shanghai
5th rowAsia/Shanghai

Common Values

ValueCountFrequency (%)
Asia/Shanghai7
 
14.3%
Europe/Oslo5
 
10.2%
America/New_York5
 
10.2%
Asia/Seoul3
 
6.1%
Asia/Tokyo3
 
6.1%
Asia/Kamchatka2
 
4.1%
Asia/Qyzylorda1
 
2.0%
(Missing)23
46.9%

Length

2022-09-05T21:45:39.794153image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:45:39.891971image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
asia/shanghai7
26.9%
europe/oslo5
19.2%
america/new_york5
19.2%
asia/seoul3
11.5%
asia/tokyo3
11.5%
asia/kamchatka2
 
7.7%
asia/qyzylorda1
 
3.8%

Most occurring characters

ValueCountFrequency (%)
a42
 
12.8%
i28
 
8.5%
/26
 
7.9%
o25
 
7.6%
A21
 
6.4%
s21
 
6.4%
e18
 
5.5%
h16
 
4.9%
r16
 
4.9%
S10
 
3.0%
Other values (21)105
32.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter240
73.2%
Uppercase Letter57
 
17.4%
Other Punctuation26
 
7.9%
Connector Punctuation5
 
1.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a42
17.5%
i28
11.7%
o25
10.4%
s21
8.8%
e18
 
7.5%
h16
 
6.7%
r16
 
6.7%
k10
 
4.2%
l9
 
3.8%
u8
 
3.3%
Other values (10)47
19.6%
Uppercase Letter
ValueCountFrequency (%)
A21
36.8%
S10
17.5%
Y5
 
8.8%
O5
 
8.8%
N5
 
8.8%
E5
 
8.8%
T3
 
5.3%
K2
 
3.5%
Q1
 
1.8%
Other Punctuation
ValueCountFrequency (%)
/26
100.0%
Connector Punctuation
ValueCountFrequency (%)
_5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin297
90.5%
Common31
 
9.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
a42
14.1%
i28
 
9.4%
o25
 
8.4%
A21
 
7.1%
s21
 
7.1%
e18
 
6.1%
h16
 
5.4%
r16
 
5.4%
S10
 
3.4%
k10
 
3.4%
Other values (19)90
30.3%
Common
ValueCountFrequency (%)
/26
83.9%
_5
 
16.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII328
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a42
 
12.8%
i28
 
8.5%
/26
 
7.9%
o25
 
7.6%
A21
 
6.4%
s21
 
6.4%
e18
 
5.5%
h16
 
4.9%
r16
 
4.9%
S10
 
3.0%
Other values (21)105
32.0%

_embedded.show.webChannel.officialSite
Categorical

HIGH CORRELATION
MISSING

Distinct9
Distinct (%)39.1%
Missing26
Missing (%)53.1%
Memory size520.0 B
https://www.youtube.com
10 
https://www.iq.com/
https://v.qq.com/
https://www.netflix.com/
https://www.vlive.tv/home
 
1
Other values (4)

Length

Max length30
Median length25
Mean length21.95652174
Min length17

Characters and Unicode

Total characters505
Distinct characters26
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)21.7%

Sample

1st rowhttps://www.vlive.tv/home
2nd rowhttps://v.qq.com/
3rd rowhttps://v.qq.com/
4th rowhttps://tv.kakao.com/top
5th rowhttps://tv.naver.com/

Common Values

ValueCountFrequency (%)
https://www.youtube.com10
 
20.4%
https://www.iq.com/4
 
8.2%
https://v.qq.com/2
 
4.1%
https://www.netflix.com/2
 
4.1%
https://www.vlive.tv/home1
 
2.0%
https://tv.kakao.com/top1
 
2.0%
https://tv.naver.com/1
 
2.0%
https://wetv.vip/1
 
2.0%
https://www.discoveryplus.com/1
 
2.0%
(Missing)26
53.1%

Length

2022-09-05T21:45:39.985067image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:45:40.083171image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
https://www.youtube.com10
43.5%
https://www.iq.com4
 
17.4%
https://v.qq.com2
 
8.7%
https://www.netflix.com2
 
8.7%
https://www.vlive.tv/home1
 
4.3%
https://tv.kakao.com/top1
 
4.3%
https://tv.naver.com1
 
4.3%
https://wetv.vip1
 
4.3%
https://www.discoveryplus.com1
 
4.3%

Most occurring characters

ValueCountFrequency (%)
t63
12.5%
/59
11.7%
w55
10.9%
.45
 
8.9%
o35
 
6.9%
p26
 
5.1%
s25
 
5.0%
h24
 
4.8%
:23
 
4.6%
m22
 
4.4%
Other values (16)128
25.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter378
74.9%
Other Punctuation127
 
25.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t63
16.7%
w55
14.6%
o35
9.3%
p26
 
6.9%
s25
 
6.6%
h24
 
6.3%
m22
 
5.8%
c22
 
5.8%
u21
 
5.6%
e17
 
4.5%
Other values (13)68
18.0%
Other Punctuation
ValueCountFrequency (%)
/59
46.5%
.45
35.4%
:23
 
18.1%

Most occurring scripts

ValueCountFrequency (%)
Latin378
74.9%
Common127
 
25.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
t63
16.7%
w55
14.6%
o35
9.3%
p26
 
6.9%
s25
 
6.6%
h24
 
6.3%
m22
 
5.8%
c22
 
5.8%
u21
 
5.6%
e17
 
4.5%
Other values (13)68
18.0%
Common
ValueCountFrequency (%)
/59
46.5%
.45
35.4%
:23
 
18.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII505
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t63
12.5%
/59
11.7%
w55
10.9%
.45
 
8.9%
o35
 
6.9%
p26
 
5.1%
s25
 
5.0%
h24
 
4.8%
:23
 
4.6%
m22
 
4.4%
Other values (16)128
25.3%

_embedded.show.dvdCountry
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing49
Missing (%)100.0%
Memory size520.0 B

_embedded.show.externals.tvrage
Categorical

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing48
Missing (%)98.0%
Memory size520.0 B
15090.0

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters7
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row15090.0

Common Values

ValueCountFrequency (%)
15090.01
 
2.0%
(Missing)48
98.0%

Length

2022-09-05T21:45:40.171383image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:45:40.244814image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
15090.01
100.0%

Most occurring characters

ValueCountFrequency (%)
03
42.9%
11
 
14.3%
51
 
14.3%
91
 
14.3%
.1
 
14.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number6
85.7%
Other Punctuation1
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
03
50.0%
11
 
16.7%
51
 
16.7%
91
 
16.7%
Other Punctuation
ValueCountFrequency (%)
.1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common7
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
03
42.9%
11
 
14.3%
51
 
14.3%
91
 
14.3%
.1
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII7
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
03
42.9%
11
 
14.3%
51
 
14.3%
91
 
14.3%
.1
 
14.3%

_embedded.show.externals.thetvdb
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct32
Distinct (%)86.5%
Missing12
Missing (%)24.5%
Infinite0
Infinite (%)0.0%
Mean359347.7838
Minimum255564
Maximum397581
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size520.0 B
2022-09-05T21:45:40.318270image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum255564
5-th percentile262312
Q1331095
median375304
Q3390342
95-th percentile397247
Maximum397581
Range142017
Interquartile range (IQR)59247

Descriptive statistics

Standard deviation42898.94769
Coefficient of variation (CV)0.1193800258
Kurtosis0.8373611093
Mean359347.7838
Median Absolute Deviation (MAD)17925
Skewness-1.339586932
Sum13295868
Variance1840319713
MonotonicityNot monotonic
2022-09-05T21:45:40.422583image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
3932292
 
4.1%
2555642
 
4.1%
3871522
 
4.1%
3310952
 
4.1%
3972472
 
4.1%
3615411
 
2.0%
3894171
 
2.0%
3226731
 
2.0%
3697981
 
2.0%
3871301
 
2.0%
Other values (22)22
44.9%
(Missing)12
24.5%
ValueCountFrequency (%)
2555642
4.1%
2639991
2.0%
2651931
2.0%
3166901
2.0%
3226731
2.0%
3227211
2.0%
3229061
2.0%
3310952
4.1%
3423291
2.0%
3560851
2.0%
ValueCountFrequency (%)
3975811
2.0%
3972472
4.1%
3966231
2.0%
3948761
2.0%
3932292
4.1%
3926491
2.0%
3908731
2.0%
3903421
2.0%
3894171
2.0%
3886721
2.0%

_embedded.show.externals.imdb
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct19
Distinct (%)86.4%
Missing27
Missing (%)55.1%
Memory size520.0 B
tt8871128
tt13175760
tt13599000
tt12457946
 
1
tt8851444
 
1
Other values (14)
14 

Length

Max length10
Median length10
Mean length9.681818182
Min length9

Characters and Unicode

Total characters213
Distinct characters11
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)72.7%

Sample

1st rowtt10784214
2nd rowtt13375866
3rd rowtt8871128
4th rowtt8871128
5th rowtt10960302

Common Values

ValueCountFrequency (%)
tt88711282
 
4.1%
tt131757602
 
4.1%
tt135990002
 
4.1%
tt124579461
 
2.0%
tt88514441
 
2.0%
tt133995381
 
2.0%
tt125849001
 
2.0%
tt96901121
 
2.0%
tt30662421
 
2.0%
tt126055481
 
2.0%
Other values (9)9
 
18.4%
(Missing)27
55.1%

Length

2022-09-05T21:45:40.518521image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
tt88711282
 
9.1%
tt135990002
 
9.1%
tt131757602
 
9.1%
tt65948821
 
4.5%
tt133758661
 
4.5%
tt109603021
 
4.5%
tt114923201
 
4.5%
tt107270441
 
4.5%
tt63440821
 
4.5%
tt107842141
 
4.5%
Other values (9)9
40.9%

Most occurring characters

ValueCountFrequency (%)
t44
20.7%
127
12.7%
024
11.3%
418
8.5%
817
 
8.0%
217
 
8.0%
615
 
7.0%
314
 
6.6%
513
 
6.1%
913
 
6.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number169
79.3%
Lowercase Letter44
 
20.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
127
16.0%
024
14.2%
418
10.7%
817
10.1%
217
10.1%
615
8.9%
314
8.3%
513
7.7%
913
7.7%
711
6.5%
Lowercase Letter
ValueCountFrequency (%)
t44
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common169
79.3%
Latin44
 
20.7%

Most frequent character per script

Common
ValueCountFrequency (%)
127
16.0%
024
14.2%
418
10.7%
817
10.1%
217
10.1%
615
8.9%
314
8.3%
513
7.7%
913
7.7%
711
6.5%
Latin
ValueCountFrequency (%)
t44
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII213
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t44
20.7%
127
12.7%
024
11.3%
418
8.5%
817
 
8.0%
217
 
8.0%
615
 
7.0%
314
 
6.6%
513
 
6.1%
913
 
6.1%

_embedded.show.image.medium
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct40
Distinct (%)87.0%
Missing3
Missing (%)6.1%
Memory size520.0 B
https://static.tvmaze.com/uploads/images/medium_portrait/291/729820.jpg
 
2
https://static.tvmaze.com/uploads/images/medium_portrait/291/729147.jpg
 
2
https://static.tvmaze.com/uploads/images/medium_portrait/51/128137.jpg
 
2
https://static.tvmaze.com/uploads/images/medium_portrait/277/693739.jpg
 
2
https://static.tvmaze.com/uploads/images/medium_portrait/255/639532.jpg
 
2
Other values (35)
36 

Length

Max length72
Median length71
Mean length71.08695652
Min length70

Characters and Unicode

Total characters3270
Distinct characters32
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique34 ?
Unique (%)73.9%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/medium_portrait/190/476668.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/medium_portrait/51/128137.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/medium_portrait/51/128137.jpg
4th rowhttps://static.tvmaze.com/uploads/images/medium_portrait/150/375304.jpg
5th rowhttps://static.tvmaze.com/uploads/images/medium_portrait/270/675333.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_portrait/291/729820.jpg2
 
4.1%
https://static.tvmaze.com/uploads/images/medium_portrait/291/729147.jpg2
 
4.1%
https://static.tvmaze.com/uploads/images/medium_portrait/51/128137.jpg2
 
4.1%
https://static.tvmaze.com/uploads/images/medium_portrait/277/693739.jpg2
 
4.1%
https://static.tvmaze.com/uploads/images/medium_portrait/255/639532.jpg2
 
4.1%
https://static.tvmaze.com/uploads/images/medium_portrait/308/770106.jpg2
 
4.1%
https://static.tvmaze.com/uploads/images/medium_portrait/190/476668.jpg1
 
2.0%
https://static.tvmaze.com/uploads/images/medium_portrait/402/1005033.jpg1
 
2.0%
https://static.tvmaze.com/uploads/images/medium_portrait/361/903289.jpg1
 
2.0%
https://static.tvmaze.com/uploads/images/medium_portrait/398/996514.jpg1
 
2.0%
Other values (30)30
61.2%
(Missing)3
 
6.1%

Length

2022-09-05T21:45:40.612445image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_portrait/291/729820.jpg2
 
4.3%
https://static.tvmaze.com/uploads/images/medium_portrait/51/128137.jpg2
 
4.3%
https://static.tvmaze.com/uploads/images/medium_portrait/277/693739.jpg2
 
4.3%
https://static.tvmaze.com/uploads/images/medium_portrait/255/639532.jpg2
 
4.3%
https://static.tvmaze.com/uploads/images/medium_portrait/308/770106.jpg2
 
4.3%
https://static.tvmaze.com/uploads/images/medium_portrait/291/729147.jpg2
 
4.3%
https://static.tvmaze.com/uploads/images/medium_portrait/344/861394.jpg1
 
2.2%
https://static.tvmaze.com/uploads/images/medium_portrait/276/691974.jpg1
 
2.2%
https://static.tvmaze.com/uploads/images/medium_portrait/275/688802.jpg1
 
2.2%
https://static.tvmaze.com/uploads/images/medium_portrait/213/533674.jpg1
 
2.2%
Other values (30)30
65.2%

Most occurring characters

ValueCountFrequency (%)
t322
 
9.8%
/322
 
9.8%
m230
 
7.0%
a230
 
7.0%
p184
 
5.6%
s184
 
5.6%
i184
 
5.6%
.138
 
4.2%
o138
 
4.2%
e138
 
4.2%
Other values (22)1200
36.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2300
70.3%
Other Punctuation506
 
15.5%
Decimal Number418
 
12.8%
Connector Punctuation46
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t322
14.0%
m230
10.0%
a230
10.0%
p184
 
8.0%
s184
 
8.0%
i184
 
8.0%
o138
 
6.0%
e138
 
6.0%
u92
 
4.0%
r92
 
4.0%
Other values (8)506
22.0%
Decimal Number
ValueCountFrequency (%)
958
13.9%
350
12.0%
747
11.2%
246
11.0%
145
10.8%
040
9.6%
837
8.9%
636
8.6%
430
7.2%
529
6.9%
Other Punctuation
ValueCountFrequency (%)
/322
63.6%
.138
27.3%
:46
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_46
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2300
70.3%
Common970
29.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
t322
14.0%
m230
10.0%
a230
10.0%
p184
 
8.0%
s184
 
8.0%
i184
 
8.0%
o138
 
6.0%
e138
 
6.0%
u92
 
4.0%
r92
 
4.0%
Other values (8)506
22.0%
Common
ValueCountFrequency (%)
/322
33.2%
.138
14.2%
958
 
6.0%
350
 
5.2%
747
 
4.8%
246
 
4.7%
_46
 
4.7%
:46
 
4.7%
145
 
4.6%
040
 
4.1%
Other values (4)132
13.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII3270
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t322
 
9.8%
/322
 
9.8%
m230
 
7.0%
a230
 
7.0%
p184
 
5.6%
s184
 
5.6%
i184
 
5.6%
.138
 
4.2%
o138
 
4.2%
e138
 
4.2%
Other values (22)1200
36.7%

_embedded.show.image.original
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct40
Distinct (%)87.0%
Missing3
Missing (%)6.1%
Memory size520.0 B
https://static.tvmaze.com/uploads/images/original_untouched/291/729820.jpg
 
2
https://static.tvmaze.com/uploads/images/original_untouched/291/729147.jpg
 
2
https://static.tvmaze.com/uploads/images/original_untouched/51/128137.jpg
 
2
https://static.tvmaze.com/uploads/images/original_untouched/277/693739.jpg
 
2
https://static.tvmaze.com/uploads/images/original_untouched/255/639532.jpg
 
2
Other values (35)
36 

Length

Max length75
Median length74
Mean length74.08695652
Min length73

Characters and Unicode

Total characters3408
Distinct characters33
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique34 ?
Unique (%)73.9%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/original_untouched/190/476668.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/original_untouched/51/128137.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/original_untouched/51/128137.jpg
4th rowhttps://static.tvmaze.com/uploads/images/original_untouched/150/375304.jpg
5th rowhttps://static.tvmaze.com/uploads/images/original_untouched/270/675333.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/291/729820.jpg2
 
4.1%
https://static.tvmaze.com/uploads/images/original_untouched/291/729147.jpg2
 
4.1%
https://static.tvmaze.com/uploads/images/original_untouched/51/128137.jpg2
 
4.1%
https://static.tvmaze.com/uploads/images/original_untouched/277/693739.jpg2
 
4.1%
https://static.tvmaze.com/uploads/images/original_untouched/255/639532.jpg2
 
4.1%
https://static.tvmaze.com/uploads/images/original_untouched/308/770106.jpg2
 
4.1%
https://static.tvmaze.com/uploads/images/original_untouched/190/476668.jpg1
 
2.0%
https://static.tvmaze.com/uploads/images/original_untouched/402/1005033.jpg1
 
2.0%
https://static.tvmaze.com/uploads/images/original_untouched/361/903289.jpg1
 
2.0%
https://static.tvmaze.com/uploads/images/original_untouched/398/996514.jpg1
 
2.0%
Other values (30)30
61.2%
(Missing)3
 
6.1%

Length

2022-09-05T21:45:40.707596image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/291/729820.jpg2
 
4.3%
https://static.tvmaze.com/uploads/images/original_untouched/51/128137.jpg2
 
4.3%
https://static.tvmaze.com/uploads/images/original_untouched/277/693739.jpg2
 
4.3%
https://static.tvmaze.com/uploads/images/original_untouched/255/639532.jpg2
 
4.3%
https://static.tvmaze.com/uploads/images/original_untouched/308/770106.jpg2
 
4.3%
https://static.tvmaze.com/uploads/images/original_untouched/291/729147.jpg2
 
4.3%
https://static.tvmaze.com/uploads/images/original_untouched/344/861394.jpg1
 
2.2%
https://static.tvmaze.com/uploads/images/original_untouched/276/691974.jpg1
 
2.2%
https://static.tvmaze.com/uploads/images/original_untouched/275/688802.jpg1
 
2.2%
https://static.tvmaze.com/uploads/images/original_untouched/213/533674.jpg1
 
2.2%
Other values (30)30
65.2%

Most occurring characters

ValueCountFrequency (%)
/322
 
9.4%
t276
 
8.1%
a230
 
6.7%
s184
 
5.4%
i184
 
5.4%
o184
 
5.4%
p138
 
4.0%
c138
 
4.0%
.138
 
4.0%
g138
 
4.0%
Other values (23)1476
43.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2438
71.5%
Other Punctuation506
 
14.8%
Decimal Number418
 
12.3%
Connector Punctuation46
 
1.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t276
 
11.3%
a230
 
9.4%
s184
 
7.5%
i184
 
7.5%
o184
 
7.5%
p138
 
5.7%
c138
 
5.7%
g138
 
5.7%
m138
 
5.7%
e138
 
5.7%
Other values (9)690
28.3%
Decimal Number
ValueCountFrequency (%)
958
13.9%
350
12.0%
747
11.2%
246
11.0%
145
10.8%
040
9.6%
837
8.9%
636
8.6%
430
7.2%
529
6.9%
Other Punctuation
ValueCountFrequency (%)
/322
63.6%
.138
27.3%
:46
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_46
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2438
71.5%
Common970
 
28.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
t276
 
11.3%
a230
 
9.4%
s184
 
7.5%
i184
 
7.5%
o184
 
7.5%
p138
 
5.7%
c138
 
5.7%
g138
 
5.7%
m138
 
5.7%
e138
 
5.7%
Other values (9)690
28.3%
Common
ValueCountFrequency (%)
/322
33.2%
.138
14.2%
958
 
6.0%
350
 
5.2%
747
 
4.8%
:46
 
4.7%
_46
 
4.7%
246
 
4.7%
145
 
4.6%
040
 
4.1%
Other values (4)132
13.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII3408
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/322
 
9.4%
t276
 
8.1%
a230
 
6.7%
s184
 
5.4%
i184
 
5.4%
o184
 
5.4%
p138
 
4.0%
c138
 
4.0%
.138
 
4.0%
g138
 
4.0%
Other values (23)1476
43.3%

_embedded.show.summary
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct40
Distinct (%)88.9%
Missing4
Missing (%)8.2%
Memory size520.0 B
<p>Curious about his uncle's past, Wu Xie watched a mysterious videotape, only to find himself mixed up in an elaborate conspiracy. In his adventures, he encountered Zhang Qi Ling, Xie Yu Chen, and others. </p>
 
2
<p>A story that follows undercover cop Gan Tian Lei who spent 10 years of his life walking a gray area. After waking up from a serious injury, he restarts his life and tries to solve a case by relying on his lost memories.</p>
 
2
<p><b>Detention</b> starts at Greenwood High School in the 1990s. Yunxiang Liu, a transfer student, steps into the forbidden area on the campus by accident, where she encounters the ghost of Ruixin Fang. Fang later unveils the hidden history and trauma over the past 30 years, and how a group of young students and teachers were persecuted as they fought for freedom in the era of censorship. Their stories keep coming back to the school like haunting nightmares, waiting to be told and revealed.  </p>
 
2
<p>The story happens at the end of the Tang Dynasty, when Zhu Wen usurps the throne and establishes the Later Liang Dynasty, and he's known as Emperor Taizu. Ma Zhai Xing (Li Qin) is the daughter of an official and as a child, she befriends a young boy (Darren Wang) who lives in the mountain. One day when he saves a wolf, he accidentally falls over the cliff and is rescued by Zhu Wen. The authoritative figure adopts him as a godson and gives him the title Bo Wang. Ten years later, he saves the female lead per chance and finds her courage and intelligence resonant, and she likes that while he's in a position of power, he still has humility and kindness. She encourages him to fight for justice and he begins that journey by helping the people, stopping throne fights, etc. Even when they have conflicts, they will face those frankly. As they overcome obstacles and fight for justice, feelings deepen and they are able to reap their own happiness by each other's side.</p>
 
2
<p>The play consists of three youth stories. "He and Meow": The cat Jiang Xiao Kui and his owner Jiang Qing from the cat kingdom live a happy life. Until Jiang Qing's younger brother Jiang Xia returned home. Xia, who was allergic to cats, and Jiang Xiao Kui, who hated his younger brother, started a battle over sister's favor. "Full-time rival": Xu Tian Yi and Li Shi Lin, who had been at odds for a long time, reunited during the summer sprint training. In the process of competing against each other, their misunderstanding was resolved. Just when the two worked together to enter the team, an accident happened. "The Man in the Story": Yu Sheng, a young man, accidentally discovered that he turned out to be a character in Xu Mo's novel. After learning about the tragic ending of himself and his sister, he came to the real world to fight with the writer in an attempt to change his destiny.</p><p><br /> </p>
 
2
Other values (35)
35 

Length

Max length1620
Median length370
Mean length423.7555556
Min length70

Characters and Unicode

Total characters19069
Distinct characters99
Distinct categories13 ?
Distinct scripts5 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique35 ?
Unique (%)77.8%

Sample

1st row<p><b>Sim for You</b> is a reality series that chronicles each EXO member's life and reveal stories from their everyday life as a series.</p>
2nd row<p>Tang San spent his life in the Tang Outer Sect, dedicated to the creation and mastery of hidden weapons. Once he stole the secret lore of the Inner Sect to reach the pinnacle of his art, his only way out was death. But after throwing himself off the deadly Hell's Peak he was reborn in a different world, the world of Douluo Dalu, a world where every person has a spirit of their own, and those with powerful spirits can practice their spirit power to rise and become Spirit Masters.<br /><br />The spirit that awakens within Tang San is Blue Silver Grass, a useless spirit. Can he overcome the difficulties to reach the high ranks of Spirit Masters and bring the glory of the Tang Sect into this new world?</p>
3rd row<p>In ancient Shenzhou, humans and demons had been in constant dispute for thousands of years. The demon princess from Tushan, Bai Binglan, and the human Zhang Kuangyun met each other due to a misunderstanding. In order to investigate the enemy country, Bai Binglan became Zhang Kuangyun's companion. As they travel together, Zhang Kuangyun discovers a conspiracy...</p>
4th row<p>"Have you heard? The rubbish Heaven Official is having an affair with the ghost realm's number one bigshot!"</p><p>Eight hundred years ago, Xie Lian was the Crown Prince of the Xian Le kingdom; one who was beloved by his citizens and the darling of the world. Unsurprisingly, he ascended to the Heavens at a very young age. Now, eight hundred years later, Xie Lian ascends to the Heavens for the third time as the laughing stock of all three realms. On his first task as a god, he meets a mysterious demon who rules the ghosts and terrifies the Heavens... yet unbeknownst to Xie Lian, this demon king has been paying attention to him for a very, very long time.</p>
5th row<p>The story happens at the end of the Tang Dynasty, when Zhu Wen usurps the throne and establishes the Later Liang Dynasty, and he's known as Emperor Taizu. Ma Zhai Xing (Li Qin) is the daughter of an official and as a child, she befriends a young boy (Darren Wang) who lives in the mountain. One day when he saves a wolf, he accidentally falls over the cliff and is rescued by Zhu Wen. The authoritative figure adopts him as a godson and gives him the title Bo Wang. Ten years later, he saves the female lead per chance and finds her courage and intelligence resonant, and she likes that while he's in a position of power, he still has humility and kindness. She encourages him to fight for justice and he begins that journey by helping the people, stopping throne fights, etc. Even when they have conflicts, they will face those frankly. As they overcome obstacles and fight for justice, feelings deepen and they are able to reap their own happiness by each other's side.</p>

Common Values

ValueCountFrequency (%)
<p>Curious about his uncle's past, Wu Xie watched a mysterious videotape, only to find himself mixed up in an elaborate conspiracy. In his adventures, he encountered Zhang Qi Ling, Xie Yu Chen, and others. </p>2
 
4.1%
<p>A story that follows undercover cop Gan Tian Lei who spent 10 years of his life walking a gray area. After waking up from a serious injury, he restarts his life and tries to solve a case by relying on his lost memories.</p>2
 
4.1%
<p><b>Detention</b> starts at Greenwood High School in the 1990s. Yunxiang Liu, a transfer student, steps into the forbidden area on the campus by accident, where she encounters the ghost of Ruixin Fang. Fang later unveils the hidden history and trauma over the past 30 years, and how a group of young students and teachers were persecuted as they fought for freedom in the era of censorship. Their stories keep coming back to the school like haunting nightmares, waiting to be told and revealed.  </p>2
 
4.1%
<p>The story happens at the end of the Tang Dynasty, when Zhu Wen usurps the throne and establishes the Later Liang Dynasty, and he's known as Emperor Taizu. Ma Zhai Xing (Li Qin) is the daughter of an official and as a child, she befriends a young boy (Darren Wang) who lives in the mountain. One day when he saves a wolf, he accidentally falls over the cliff and is rescued by Zhu Wen. The authoritative figure adopts him as a godson and gives him the title Bo Wang. Ten years later, he saves the female lead per chance and finds her courage and intelligence resonant, and she likes that while he's in a position of power, he still has humility and kindness. She encourages him to fight for justice and he begins that journey by helping the people, stopping throne fights, etc. Even when they have conflicts, they will face those frankly. As they overcome obstacles and fight for justice, feelings deepen and they are able to reap their own happiness by each other's side.</p>2
 
4.1%
<p>The play consists of three youth stories. "He and Meow": The cat Jiang Xiao Kui and his owner Jiang Qing from the cat kingdom live a happy life. Until Jiang Qing's younger brother Jiang Xia returned home. Xia, who was allergic to cats, and Jiang Xiao Kui, who hated his younger brother, started a battle over sister's favor. "Full-time rival": Xu Tian Yi and Li Shi Lin, who had been at odds for a long time, reunited during the summer sprint training. In the process of competing against each other, their misunderstanding was resolved. Just when the two worked together to enter the team, an accident happened. "The Man in the Story": Yu Sheng, a young man, accidentally discovered that he turned out to be a character in Xu Mo's novel. After learning about the tragic ending of himself and his sister, he came to the real world to fight with the writer in an attempt to change his destiny.</p><p><br /> </p>2
 
4.1%
<p>Long ago, the Book of Ancients was the transcriber of history, recording everything known to man; myths, creatures, stories, science and technology, humanity evolved, civilization ... It was protected by the Sword of Logos, a sect of swordsmen tasked with protecting the book to keep the world in balance. However, thousands of years ago, the Megiddo attacked and tried to steal it. As a result, the Book vanished, and each of its pages scattered across the world. In the present day, young novelist Touma Kamiyama has been having dreams of another dimension, swordsmen and monsters coming out of a storybook, and a "mysterious girl" calling for help. Recalling the dream sends chills down his spine, not knowing anything about the dream. One day, a strange phenomenon occurred without notice; a part of the city disappeared, people's loved ones disappear one after another, and sends the entire nation into chaos. The vanished part of the city appeared in an alternate dimension, called Wonder World, an endless dimension as big as pages from a book. The dimension is home to magical creatures that attack without hesitation, sending the people in fear and confusion. As Touma and Mei are caught in this phenomenon, the attack reminds Touma of his dream as he is attacked by a mysterious monster. "I will definitely bring the city back to the original world!" As if it was responding to his very will, Touma harnesses the power of the red Dragon as it merges into his body, turning him into the Swordsman of Fire. The battle between the real world and Wonder World has an ending, and its destiny is in his hands.</p>1
 
2.0%
<p>The web series revolves around the life of university students.</p>1
 
2.0%
<p><b>I Like to Watch</b> is a 2019 American web series hosted by drag queens Trixie Mattel and Katya Zamolodchikova. The series was created by Fran Tirado, produced by Netflix, and streams on the network's YouTube channel. Produced in a similar format to Mattel and Zamolodchikova's web series <i>UNHhhh</i> and <i>The Trixie &amp; Katya Show</i>, <i>I Like to Watch</i> follows its hosts as they view and react to various Netflix Original Programming.</p>1
 
2.0%
<p>Destination UA is the project showing Ukraine from foreigner's perspective.</p><p>In First season we spent 30 days traveling along the tourist route called Golden Triangle – Kyiv-Lviv-Odesa.</p><p>We've visited more than 100 locations, tried over two dozen unique Ukrainian dishes, filmed ancient history places and modern spots. We had a lot of fun.</p><p>In the second season of the show we are visited next regions: Kyiv, Chernihiv, Sumy, Kharkiv, Poltava, Dnipro, Kherson, Mykolaiv, Vinnytsia, Zhytomyr.</p><p>Next 100 locations, interesting facts, adventures are waiting for you.</p>1
 
2.0%
<p>FUN EDUCATIONAL videos for children! Kids will learn colors, learn shapes, learn numbers, learn letters, the alphabet, abc's and so much more with Blippi's nursery rhymes, educational songs, and educational videos! Blippi ties in things children love like Backhoes, Tractors, Planes, Trains, Animals, Boats, Unicorns, Construction Equipment, Firetrucks, Horses, and the list goes on! Incorporating cartoons and animation with real life footage!</p>1
 
2.0%
Other values (30)30
61.2%
(Missing)4
 
8.2%

Length

2022-09-05T21:45:40.827453image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the197
 
6.2%
and119
 
3.8%
a91
 
2.9%
of82
 
2.6%
to78
 
2.5%
in57
 
1.8%
his37
 
1.2%
he31
 
1.0%
as30
 
0.9%
is28
 
0.9%
Other values (1235)2413
76.3%

Most occurring characters

ValueCountFrequency (%)
3107
16.3%
e1707
 
9.0%
a1238
 
6.5%
t1237
 
6.5%
i1098
 
5.8%
n1088
 
5.7%
o1078
 
5.7%
s970
 
5.1%
r904
 
4.7%
h783
 
4.1%
Other values (89)5859
30.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter14325
75.1%
Space Separator3120
 
16.4%
Uppercase Letter647
 
3.4%
Other Punctuation556
 
2.9%
Math Symbol316
 
1.7%
Decimal Number43
 
0.2%
Dash Punctuation35
 
0.2%
Close Punctuation8
 
< 0.1%
Open Punctuation8
 
< 0.1%
Other Letter8
 
< 0.1%
Other values (3)3
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e1707
11.9%
a1238
 
8.6%
t1237
 
8.6%
i1098
 
7.7%
n1088
 
7.6%
o1078
 
7.5%
s970
 
6.8%
r904
 
6.3%
h783
 
5.5%
d563
 
3.9%
Other values (24)3659
25.5%
Uppercase Letter
ValueCountFrequency (%)
T72
 
11.1%
S55
 
8.5%
L40
 
6.2%
F39
 
6.0%
A35
 
5.4%
W33
 
5.1%
M28
 
4.3%
I28
 
4.3%
C27
 
4.2%
H26
 
4.0%
Other values (17)264
40.8%
Other Punctuation
ValueCountFrequency (%)
,223
40.1%
.149
26.8%
/82
 
14.7%
'43
 
7.7%
"28
 
5.0%
!13
 
2.3%
:10
 
1.8%
;4
 
0.7%
?3
 
0.5%
&1
 
0.2%
Other Letter
ValueCountFrequency (%)
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
Decimal Number
ValueCountFrequency (%)
016
37.2%
110
23.3%
97
16.3%
35
 
11.6%
24
 
9.3%
41
 
2.3%
Dash Punctuation
ValueCountFrequency (%)
-27
77.1%
7
 
20.0%
1
 
2.9%
Space Separator
ValueCountFrequency (%)
3107
99.6%
 13
 
0.4%
Math Symbol
ValueCountFrequency (%)
<158
50.0%
>158
50.0%
Close Punctuation
ValueCountFrequency (%)
)7
87.5%
]1
 
12.5%
Open Punctuation
ValueCountFrequency (%)
(7
87.5%
[1
 
12.5%
Modifier Letter
ValueCountFrequency (%)
1
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%
Initial Punctuation
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin14963
78.5%
Common4089
 
21.4%
Cyrillic9
 
< 0.1%
Han4
 
< 0.1%
Katakana4
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e1707
 
11.4%
a1238
 
8.3%
t1237
 
8.3%
i1098
 
7.3%
n1088
 
7.3%
o1078
 
7.2%
s970
 
6.5%
r904
 
6.0%
h783
 
5.2%
d563
 
3.8%
Other values (44)4297
28.7%
Common
ValueCountFrequency (%)
3107
76.0%
,223
 
5.5%
<158
 
3.9%
>158
 
3.9%
.149
 
3.6%
/82
 
2.0%
'43
 
1.1%
"28
 
0.7%
-27
 
0.7%
016
 
0.4%
Other values (20)98
 
2.4%
Cyrillic
ValueCountFrequency (%)
о3
33.3%
й1
 
11.1%
м1
 
11.1%
д1
 
11.1%
у1
 
11.1%
ч1
 
11.1%
Х1
 
11.1%
Han
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%
Katakana
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII19026
99.8%
None15
 
0.1%
Punctuation9
 
< 0.1%
Cyrillic9
 
< 0.1%
Katakana5
 
< 0.1%
CJK4
 
< 0.1%
Dingbats1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3107
16.3%
e1707
 
9.0%
a1238
 
6.5%
t1237
 
6.5%
i1098
 
5.8%
n1088
 
5.7%
o1078
 
5.7%
s970
 
5.1%
r904
 
4.8%
h783
 
4.1%
Other values (66)5816
30.6%
None
ValueCountFrequency (%)
 13
86.7%
ā1
 
6.7%
æ1
 
6.7%
Punctuation
ValueCountFrequency (%)
7
77.8%
1
 
11.1%
1
 
11.1%
Cyrillic
ValueCountFrequency (%)
о3
33.3%
й1
 
11.1%
м1
 
11.1%
д1
 
11.1%
у1
 
11.1%
ч1
 
11.1%
Х1
 
11.1%
CJK
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%
Katakana
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%
Dingbats
ValueCountFrequency (%)
1
100.0%

_embedded.show.updated
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct43
Distinct (%)87.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1644902154
Minimum1608499007
Maximum1662275668
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size520.0 B
2022-09-05T21:45:40.940284image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1608499007
5-th percentile1609887201
Q11636398937
median1649680350
Q31658922268
95-th percentile1662164069
Maximum1662275668
Range53776661
Interquartile range (IQR)22523331

Descriptive statistics

Standard deviation16914758.66
Coefficient of variation (CV)0.01028313971
Kurtosis-0.2383242198
Mean1644902154
Median Absolute Deviation (MAD)11426362
Skewness-0.9709845894
Sum8.060020554 × 1010
Variance2.861090606 × 1014
MonotonicityNot monotonic
2022-09-05T21:45:41.055028image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
16098872012
 
4.1%
16482170292
 
4.1%
16620631392
 
4.1%
16549764112
 
4.1%
16184666822
 
4.1%
16491780842
 
4.1%
16457531591
 
2.0%
16464889081
 
2.0%
16093598271
 
2.0%
16380646181
 
2.0%
Other values (33)33
67.3%
ValueCountFrequency (%)
16084990071
2.0%
16093598271
2.0%
16098872012
4.1%
16114368421
2.0%
16184666822
4.1%
16238295291
2.0%
16238296751
2.0%
16246469541
2.0%
16328615041
2.0%
16363620841
2.0%
ValueCountFrequency (%)
16622756681
2.0%
16622629611
2.0%
16622313551
2.0%
16620631392
4.1%
16616981471
2.0%
16616661431
2.0%
16611090651
2.0%
16611076721
2.0%
16611067121
2.0%
16609951231
2.0%

_embedded.show._links.self.href
Categorical

HIGH CORRELATION
UNIFORM

Distinct43
Distinct (%)87.8%
Missing0
Missing (%)0.0%
Memory size520.0 B
https://api.tvmaze.com/shows/51125
 
2
https://api.tvmaze.com/shows/47912
 
2
https://api.tvmaze.com/shows/10892
 
2
https://api.tvmaze.com/shows/52743
 
2
https://api.tvmaze.com/shows/54762
 
2
Other values (38)
39 

Length

Max length34
Median length34
Mean length33.95918367
Min length33

Characters and Unicode

Total characters1664
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique37 ?
Unique (%)75.5%

Sample

1st rowhttps://api.tvmaze.com/shows/41648
2nd rowhttps://api.tvmaze.com/shows/10892
3rd rowhttps://api.tvmaze.com/shows/10892
4th rowhttps://api.tvmaze.com/shows/35551
5th rowhttps://api.tvmaze.com/shows/49206

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/shows/511252
 
4.1%
https://api.tvmaze.com/shows/479122
 
4.1%
https://api.tvmaze.com/shows/108922
 
4.1%
https://api.tvmaze.com/shows/527432
 
4.1%
https://api.tvmaze.com/shows/547622
 
4.1%
https://api.tvmaze.com/shows/528062
 
4.1%
https://api.tvmaze.com/shows/509391
 
2.0%
https://api.tvmaze.com/shows/608481
 
2.0%
https://api.tvmaze.com/shows/489221
 
2.0%
https://api.tvmaze.com/shows/535641
 
2.0%
Other values (33)33
67.3%

Length

2022-09-05T21:45:41.147987image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/shows/511252
 
4.1%
https://api.tvmaze.com/shows/108922
 
4.1%
https://api.tvmaze.com/shows/527432
 
4.1%
https://api.tvmaze.com/shows/547622
 
4.1%
https://api.tvmaze.com/shows/528062
 
4.1%
https://api.tvmaze.com/shows/479122
 
4.1%
https://api.tvmaze.com/shows/566051
 
2.0%
https://api.tvmaze.com/shows/355511
 
2.0%
https://api.tvmaze.com/shows/492061
 
2.0%
https://api.tvmaze.com/shows/497401
 
2.0%
Other values (33)33
67.3%

Most occurring characters

ValueCountFrequency (%)
/196
 
11.8%
s147
 
8.8%
t147
 
8.8%
h98
 
5.9%
p98
 
5.9%
a98
 
5.9%
o98
 
5.9%
.98
 
5.9%
m98
 
5.9%
e49
 
2.9%
Other values (16)537
32.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1078
64.8%
Other Punctuation343
 
20.6%
Decimal Number243
 
14.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s147
13.6%
t147
13.6%
h98
9.1%
p98
9.1%
a98
9.1%
o98
9.1%
m98
9.1%
e49
 
4.5%
w49
 
4.5%
c49
 
4.5%
Other values (3)147
13.6%
Decimal Number
ValueCountFrequency (%)
544
18.1%
427
11.1%
626
10.7%
123
9.5%
023
9.5%
922
9.1%
221
8.6%
820
8.2%
319
7.8%
718
7.4%
Other Punctuation
ValueCountFrequency (%)
/196
57.1%
.98
28.6%
:49
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin1078
64.8%
Common586
35.2%

Most frequent character per script

Common
ValueCountFrequency (%)
/196
33.4%
.98
16.7%
:49
 
8.4%
544
 
7.5%
427
 
4.6%
626
 
4.4%
123
 
3.9%
023
 
3.9%
922
 
3.8%
221
 
3.6%
Other values (3)57
 
9.7%
Latin
ValueCountFrequency (%)
s147
13.6%
t147
13.6%
h98
9.1%
p98
9.1%
a98
9.1%
o98
9.1%
m98
9.1%
e49
 
4.5%
w49
 
4.5%
c49
 
4.5%
Other values (3)147
13.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII1664
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/196
 
11.8%
s147
 
8.8%
t147
 
8.8%
h98
 
5.9%
p98
 
5.9%
a98
 
5.9%
o98
 
5.9%
.98
 
5.9%
m98
 
5.9%
e49
 
2.9%
Other values (16)537
32.3%

_embedded.show._links.previousepisode.href
Categorical

HIGH CORRELATION
UNIFORM

Distinct43
Distinct (%)87.8%
Missing0
Missing (%)0.0%
Memory size520.0 B
https://api.tvmaze.com/episodes/1992714
 
2
https://api.tvmaze.com/episodes/1972591
 
2
https://api.tvmaze.com/episodes/2382770
 
2
https://api.tvmaze.com/episodes/1997552
 
2
https://api.tvmaze.com/episodes/2071494
 
2
Other values (38)
39 

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters1911
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique37 ?
Unique (%)75.5%

Sample

1st rowhttps://api.tvmaze.com/episodes/1988862
2nd rowhttps://api.tvmaze.com/episodes/2382770
3rd rowhttps://api.tvmaze.com/episodes/2382770
4th rowhttps://api.tvmaze.com/episodes/2330393
5th rowhttps://api.tvmaze.com/episodes/2386129

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/19927142
 
4.1%
https://api.tvmaze.com/episodes/19725912
 
4.1%
https://api.tvmaze.com/episodes/23827702
 
4.1%
https://api.tvmaze.com/episodes/19975522
 
4.1%
https://api.tvmaze.com/episodes/20714942
 
4.1%
https://api.tvmaze.com/episodes/20000832
 
4.1%
https://api.tvmaze.com/episodes/19432811
 
2.0%
https://api.tvmaze.com/episodes/22894181
 
2.0%
https://api.tvmaze.com/episodes/19903521
 
2.0%
https://api.tvmaze.com/episodes/20312051
 
2.0%
Other values (33)33
67.3%

Length

2022-09-05T21:45:41.226049image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/19927142
 
4.1%
https://api.tvmaze.com/episodes/23827702
 
4.1%
https://api.tvmaze.com/episodes/19975522
 
4.1%
https://api.tvmaze.com/episodes/20714942
 
4.1%
https://api.tvmaze.com/episodes/20000832
 
4.1%
https://api.tvmaze.com/episodes/19725912
 
4.1%
https://api.tvmaze.com/episodes/21376061
 
2.0%
https://api.tvmaze.com/episodes/23303931
 
2.0%
https://api.tvmaze.com/episodes/23861291
 
2.0%
https://api.tvmaze.com/episodes/23773771
 
2.0%
Other values (33)33
67.3%

Most occurring characters

ValueCountFrequency (%)
/196
 
10.3%
t147
 
7.7%
p147
 
7.7%
s147
 
7.7%
e147
 
7.7%
a98
 
5.1%
i98
 
5.1%
.98
 
5.1%
m98
 
5.1%
o98
 
5.1%
Other values (16)637
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1225
64.1%
Other Punctuation343
 
17.9%
Decimal Number343
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t147
12.0%
p147
12.0%
s147
12.0%
e147
12.0%
a98
8.0%
i98
8.0%
m98
8.0%
o98
8.0%
h49
 
4.0%
d49
 
4.0%
Other values (3)147
12.0%
Decimal Number
ValueCountFrequency (%)
267
19.5%
147
13.7%
342
12.2%
741
12.0%
935
10.2%
833
9.6%
025
 
7.3%
419
 
5.5%
519
 
5.5%
615
 
4.4%
Other Punctuation
ValueCountFrequency (%)
/196
57.1%
.98
28.6%
:49
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin1225
64.1%
Common686
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/196
28.6%
.98
14.3%
267
 
9.8%
:49
 
7.1%
147
 
6.9%
342
 
6.1%
741
 
6.0%
935
 
5.1%
833
 
4.8%
025
 
3.6%
Other values (3)53
 
7.7%
Latin
ValueCountFrequency (%)
t147
12.0%
p147
12.0%
s147
12.0%
e147
12.0%
a98
8.0%
i98
8.0%
m98
8.0%
o98
8.0%
h49
 
4.0%
d49
 
4.0%
Other values (3)147
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII1911
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/196
 
10.3%
t147
 
7.7%
p147
 
7.7%
s147
 
7.7%
e147
 
7.7%
a98
 
5.1%
i98
 
5.1%
.98
 
5.1%
m98
 
5.1%
o98
 
5.1%
Other values (16)637
33.3%

image.medium
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct15
Distinct (%)100.0%
Missing34
Missing (%)69.4%
Memory size520.0 B
https://static.tvmaze.com/uploads/images/medium_landscape/290/726419.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/290/726420.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/290/726353.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/288/721858.jpg
 
1
https://static.tvmaze.com/uploads/images/medium_landscape/361/903574.jpg
 
1
Other values (10)
10 

Length

Max length73
Median length72
Mean length72.06666667
Min length72

Characters and Unicode

Total characters1081
Distinct characters32
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)100.0%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/medium_landscape/290/726419.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/medium_landscape/290/726420.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/medium_landscape/290/726353.jpg
4th rowhttps://static.tvmaze.com/uploads/images/medium_landscape/288/721858.jpg
5th rowhttps://static.tvmaze.com/uploads/images/medium_landscape/361/903574.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_landscape/290/726419.jpg1
 
2.0%
https://static.tvmaze.com/uploads/images/medium_landscape/290/726420.jpg1
 
2.0%
https://static.tvmaze.com/uploads/images/medium_landscape/290/726353.jpg1
 
2.0%
https://static.tvmaze.com/uploads/images/medium_landscape/288/721858.jpg1
 
2.0%
https://static.tvmaze.com/uploads/images/medium_landscape/361/903574.jpg1
 
2.0%
https://static.tvmaze.com/uploads/images/medium_landscape/292/731119.jpg1
 
2.0%
https://static.tvmaze.com/uploads/images/medium_landscape/288/721376.jpg1
 
2.0%
https://static.tvmaze.com/uploads/images/medium_landscape/289/724599.jpg1
 
2.0%
https://static.tvmaze.com/uploads/images/medium_landscape/289/724600.jpg1
 
2.0%
https://static.tvmaze.com/uploads/images/medium_landscape/289/724853.jpg1
 
2.0%
Other values (5)5
 
10.2%
(Missing)34
69.4%

Length

2022-09-05T21:45:41.311227image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_landscape/290/726419.jpg1
 
6.7%
https://static.tvmaze.com/uploads/images/medium_landscape/290/726420.jpg1
 
6.7%
https://static.tvmaze.com/uploads/images/medium_landscape/290/726353.jpg1
 
6.7%
https://static.tvmaze.com/uploads/images/medium_landscape/288/721858.jpg1
 
6.7%
https://static.tvmaze.com/uploads/images/medium_landscape/361/903574.jpg1
 
6.7%
https://static.tvmaze.com/uploads/images/medium_landscape/292/731119.jpg1
 
6.7%
https://static.tvmaze.com/uploads/images/medium_landscape/288/721376.jpg1
 
6.7%
https://static.tvmaze.com/uploads/images/medium_landscape/289/724599.jpg1
 
6.7%
https://static.tvmaze.com/uploads/images/medium_landscape/289/724600.jpg1
 
6.7%
https://static.tvmaze.com/uploads/images/medium_landscape/289/724853.jpg1
 
6.7%
Other values (5)5
33.3%

Most occurring characters

ValueCountFrequency (%)
/105
 
9.7%
a90
 
8.3%
t75
 
6.9%
s75
 
6.9%
m75
 
6.9%
p60
 
5.6%
e60
 
5.6%
.45
 
4.2%
c45
 
4.2%
d45
 
4.2%
Other values (22)406
37.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter765
70.8%
Other Punctuation165
 
15.3%
Decimal Number136
 
12.6%
Connector Punctuation15
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a90
11.8%
t75
9.8%
s75
9.8%
m75
9.8%
p60
 
7.8%
e60
 
7.8%
c45
 
5.9%
d45
 
5.9%
i45
 
5.9%
g30
 
3.9%
Other values (8)165
21.6%
Decimal Number
ValueCountFrequency (%)
229
21.3%
916
11.8%
816
11.8%
715
11.0%
013
9.6%
111
 
8.1%
311
 
8.1%
610
 
7.4%
410
 
7.4%
55
 
3.7%
Other Punctuation
ValueCountFrequency (%)
/105
63.6%
.45
27.3%
:15
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin765
70.8%
Common316
29.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
a90
11.8%
t75
9.8%
s75
9.8%
m75
9.8%
p60
 
7.8%
e60
 
7.8%
c45
 
5.9%
d45
 
5.9%
i45
 
5.9%
g30
 
3.9%
Other values (8)165
21.6%
Common
ValueCountFrequency (%)
/105
33.2%
.45
14.2%
229
 
9.2%
916
 
5.1%
816
 
5.1%
_15
 
4.7%
:15
 
4.7%
715
 
4.7%
013
 
4.1%
111
 
3.5%
Other values (4)36
 
11.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII1081
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/105
 
9.7%
a90
 
8.3%
t75
 
6.9%
s75
 
6.9%
m75
 
6.9%
p60
 
5.6%
e60
 
5.6%
.45
 
4.2%
c45
 
4.2%
d45
 
4.2%
Other values (22)406
37.6%

image.original
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct15
Distinct (%)100.0%
Missing34
Missing (%)69.4%
Memory size520.0 B
https://static.tvmaze.com/uploads/images/original_untouched/290/726419.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/290/726420.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/290/726353.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/288/721858.jpg
 
1
https://static.tvmaze.com/uploads/images/original_untouched/361/903574.jpg
 
1
Other values (10)
10 

Length

Max length75
Median length74
Mean length74.06666667
Min length74

Characters and Unicode

Total characters1111
Distinct characters33
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)100.0%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/original_untouched/290/726419.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/original_untouched/290/726420.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/original_untouched/290/726353.jpg
4th rowhttps://static.tvmaze.com/uploads/images/original_untouched/288/721858.jpg
5th rowhttps://static.tvmaze.com/uploads/images/original_untouched/361/903574.jpg

Common Values

ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/290/726419.jpg1
 
2.0%
https://static.tvmaze.com/uploads/images/original_untouched/290/726420.jpg1
 
2.0%
https://static.tvmaze.com/uploads/images/original_untouched/290/726353.jpg1
 
2.0%
https://static.tvmaze.com/uploads/images/original_untouched/288/721858.jpg1
 
2.0%
https://static.tvmaze.com/uploads/images/original_untouched/361/903574.jpg1
 
2.0%
https://static.tvmaze.com/uploads/images/original_untouched/292/731119.jpg1
 
2.0%
https://static.tvmaze.com/uploads/images/original_untouched/288/721376.jpg1
 
2.0%
https://static.tvmaze.com/uploads/images/original_untouched/289/724599.jpg1
 
2.0%
https://static.tvmaze.com/uploads/images/original_untouched/289/724600.jpg1
 
2.0%
https://static.tvmaze.com/uploads/images/original_untouched/289/724853.jpg1
 
2.0%
Other values (5)5
 
10.2%
(Missing)34
69.4%

Length

2022-09-05T21:45:41.398492image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/290/726419.jpg1
 
6.7%
https://static.tvmaze.com/uploads/images/original_untouched/290/726420.jpg1
 
6.7%
https://static.tvmaze.com/uploads/images/original_untouched/290/726353.jpg1
 
6.7%
https://static.tvmaze.com/uploads/images/original_untouched/288/721858.jpg1
 
6.7%
https://static.tvmaze.com/uploads/images/original_untouched/361/903574.jpg1
 
6.7%
https://static.tvmaze.com/uploads/images/original_untouched/292/731119.jpg1
 
6.7%
https://static.tvmaze.com/uploads/images/original_untouched/288/721376.jpg1
 
6.7%
https://static.tvmaze.com/uploads/images/original_untouched/289/724599.jpg1
 
6.7%
https://static.tvmaze.com/uploads/images/original_untouched/289/724600.jpg1
 
6.7%
https://static.tvmaze.com/uploads/images/original_untouched/289/724853.jpg1
 
6.7%
Other values (5)5
33.3%

Most occurring characters

ValueCountFrequency (%)
/105
 
9.5%
t90
 
8.1%
a75
 
6.8%
s60
 
5.4%
i60
 
5.4%
o60
 
5.4%
p45
 
4.1%
c45
 
4.1%
.45
 
4.1%
g45
 
4.1%
Other values (23)481
43.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter795
71.6%
Other Punctuation165
 
14.9%
Decimal Number136
 
12.2%
Connector Punctuation15
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t90
 
11.3%
a75
 
9.4%
s60
 
7.5%
i60
 
7.5%
o60
 
7.5%
p45
 
5.7%
c45
 
5.7%
g45
 
5.7%
m45
 
5.7%
e45
 
5.7%
Other values (9)225
28.3%
Decimal Number
ValueCountFrequency (%)
229
21.3%
916
11.8%
816
11.8%
715
11.0%
013
9.6%
111
 
8.1%
311
 
8.1%
610
 
7.4%
410
 
7.4%
55
 
3.7%
Other Punctuation
ValueCountFrequency (%)
/105
63.6%
.45
27.3%
:15
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin795
71.6%
Common316
 
28.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
t90
 
11.3%
a75
 
9.4%
s60
 
7.5%
i60
 
7.5%
o60
 
7.5%
p45
 
5.7%
c45
 
5.7%
g45
 
5.7%
m45
 
5.7%
e45
 
5.7%
Other values (9)225
28.3%
Common
ValueCountFrequency (%)
/105
33.2%
.45
14.2%
229
 
9.2%
916
 
5.1%
816
 
5.1%
:15
 
4.7%
_15
 
4.7%
715
 
4.7%
013
 
4.1%
111
 
3.5%
Other values (4)36
 
11.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII1111
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/105
 
9.5%
t90
 
8.1%
a75
 
6.8%
s60
 
5.4%
i60
 
5.4%
o60
 
5.4%
p45
 
4.1%
c45
 
4.1%
.45
 
4.1%
g45
 
4.1%
Other values (23)481
43.3%

_embedded.show._links.nextepisode.href
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct5
Distinct (%)100.0%
Missing44
Missing (%)89.8%
Memory size520.0 B
https://api.tvmaze.com/episodes/2330394
https://api.tvmaze.com/episodes/2377378
https://api.tvmaze.com/episodes/2373586
https://api.tvmaze.com/episodes/2377389
https://api.tvmaze.com/episodes/2343875

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters195
Distinct characters25
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)100.0%

Sample

1st rowhttps://api.tvmaze.com/episodes/2330394
2nd rowhttps://api.tvmaze.com/episodes/2377378
3rd rowhttps://api.tvmaze.com/episodes/2373586
4th rowhttps://api.tvmaze.com/episodes/2377389
5th rowhttps://api.tvmaze.com/episodes/2343875

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/23303941
 
2.0%
https://api.tvmaze.com/episodes/23773781
 
2.0%
https://api.tvmaze.com/episodes/23735861
 
2.0%
https://api.tvmaze.com/episodes/23773891
 
2.0%
https://api.tvmaze.com/episodes/23438751
 
2.0%
(Missing)44
89.8%

Length

2022-09-05T21:45:41.483177image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:45:41.571008image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/23303941
20.0%
https://api.tvmaze.com/episodes/23773781
20.0%
https://api.tvmaze.com/episodes/23735861
20.0%
https://api.tvmaze.com/episodes/23773891
20.0%
https://api.tvmaze.com/episodes/23438751
20.0%

Most occurring characters

ValueCountFrequency (%)
/20
 
10.3%
e15
 
7.7%
p15
 
7.7%
s15
 
7.7%
t15
 
7.7%
311
 
5.6%
o10
 
5.1%
a10
 
5.1%
i10
 
5.1%
.10
 
5.1%
Other values (15)64
32.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter125
64.1%
Other Punctuation35
 
17.9%
Decimal Number35
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e15
12.0%
p15
12.0%
s15
12.0%
t15
12.0%
o10
8.0%
a10
8.0%
i10
8.0%
m10
8.0%
d5
 
4.0%
h5
 
4.0%
Other values (3)15
12.0%
Decimal Number
ValueCountFrequency (%)
311
31.4%
77
20.0%
25
14.3%
84
 
11.4%
92
 
5.7%
42
 
5.7%
52
 
5.7%
01
 
2.9%
61
 
2.9%
Other Punctuation
ValueCountFrequency (%)
/20
57.1%
.10
28.6%
:5
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin125
64.1%
Common70
35.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e15
12.0%
p15
12.0%
s15
12.0%
t15
12.0%
o10
8.0%
a10
8.0%
i10
8.0%
m10
8.0%
d5
 
4.0%
h5
 
4.0%
Other values (3)15
12.0%
Common
ValueCountFrequency (%)
/20
28.6%
311
15.7%
.10
14.3%
77
 
10.0%
25
 
7.1%
:5
 
7.1%
84
 
5.7%
92
 
2.9%
42
 
2.9%
52
 
2.9%
Other values (2)2
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII195
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/20
 
10.3%
e15
 
7.7%
p15
 
7.7%
s15
 
7.7%
t15
 
7.7%
311
 
5.6%
o10
 
5.1%
a10
 
5.1%
i10
 
5.1%
.10
 
5.1%
Other values (15)64
32.8%

_embedded.show.image
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing49
Missing (%)100.0%
Memory size520.0 B

_embedded.show.webChannel.country
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing49
Missing (%)100.0%
Memory size520.0 B

_embedded.show.network.id
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct3
Distinct (%)100.0%
Missing46
Missing (%)93.9%
Memory size520.0 B
263.0
76.0
236.0

Length

Max length5
Median length5
Mean length4.666666667
Min length4

Characters and Unicode

Total characters14
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)100.0%

Sample

1st row263.0
2nd row76.0
3rd row236.0

Common Values

ValueCountFrequency (%)
263.01
 
2.0%
76.01
 
2.0%
236.01
 
2.0%
(Missing)46
93.9%

Length

2022-09-05T21:45:41.656775image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:45:41.743868image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
263.01
33.3%
76.01
33.3%
236.01
33.3%

Most occurring characters

ValueCountFrequency (%)
63
21.4%
.3
21.4%
03
21.4%
22
14.3%
32
14.3%
71
 
7.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number11
78.6%
Other Punctuation3
 
21.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
63
27.3%
03
27.3%
22
18.2%
32
18.2%
71
 
9.1%
Other Punctuation
ValueCountFrequency (%)
.3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common14
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
63
21.4%
.3
21.4%
03
21.4%
22
14.3%
32
14.3%
71
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII14
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
63
21.4%
.3
21.4%
03
21.4%
22
14.3%
32
14.3%
71
 
7.1%

_embedded.show.network.name
Categorical

HIGH CORRELATION
MISSING
UNIFORM

Distinct3
Distinct (%)100.0%
Missing46
Missing (%)93.9%
Memory size520.0 B
TV Asahi
TV Tokyo
Oprah Winfrey Network

Length

Max length21
Median length8
Mean length12.33333333
Min length8

Characters and Unicode

Total characters37
Distinct characters21
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)100.0%

Sample

1st rowTV Asahi
2nd rowTV Tokyo
3rd rowOprah Winfrey Network

Common Values

ValueCountFrequency (%)
TV Asahi1
 
2.0%
TV Tokyo1
 
2.0%
Oprah Winfrey Network1
 
2.0%
(Missing)46
93.9%

Length

2022-09-05T21:45:41.825471image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:45:41.912353image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
tv2
28.6%
asahi1
14.3%
tokyo1
14.3%
oprah1
14.3%
winfrey1
14.3%
network1
14.3%

Most occurring characters

ValueCountFrequency (%)
4
 
10.8%
T3
 
8.1%
o3
 
8.1%
r3
 
8.1%
e2
 
5.4%
V2
 
5.4%
k2
 
5.4%
y2
 
5.4%
i2
 
5.4%
h2
 
5.4%
Other values (11)12
32.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter24
64.9%
Uppercase Letter9
 
24.3%
Space Separator4
 
10.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o3
12.5%
r3
12.5%
e2
8.3%
k2
8.3%
y2
8.3%
i2
8.3%
h2
8.3%
a2
8.3%
p1
 
4.2%
s1
 
4.2%
Other values (4)4
16.7%
Uppercase Letter
ValueCountFrequency (%)
T3
33.3%
V2
22.2%
O1
 
11.1%
W1
 
11.1%
A1
 
11.1%
N1
 
11.1%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin33
89.2%
Common4
 
10.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
T3
 
9.1%
o3
 
9.1%
r3
 
9.1%
e2
 
6.1%
V2
 
6.1%
k2
 
6.1%
y2
 
6.1%
i2
 
6.1%
h2
 
6.1%
a2
 
6.1%
Other values (10)10
30.3%
Common
ValueCountFrequency (%)
4
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII37
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4
 
10.8%
T3
 
8.1%
o3
 
8.1%
r3
 
8.1%
e2
 
5.4%
V2
 
5.4%
k2
 
5.4%
y2
 
5.4%
i2
 
5.4%
h2
 
5.4%
Other values (11)12
32.4%

_embedded.show.network.country.name
Categorical

HIGH CORRELATION
MISSING

Distinct2
Distinct (%)66.7%
Missing46
Missing (%)93.9%
Memory size520.0 B
Japan
United States

Length

Max length13
Median length5
Mean length7.666666667
Min length5

Characters and Unicode

Total characters23
Distinct characters12
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)33.3%

Sample

1st rowJapan
2nd rowJapan
3rd rowUnited States

Common Values

ValueCountFrequency (%)
Japan2
 
4.1%
United States1
 
2.0%
(Missing)46
93.9%

Length

2022-09-05T21:45:42.002546image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:45:42.088598image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
japan2
50.0%
united1
25.0%
states1
25.0%

Most occurring characters

ValueCountFrequency (%)
a5
21.7%
n3
13.0%
t3
13.0%
J2
 
8.7%
p2
 
8.7%
e2
 
8.7%
U1
 
4.3%
i1
 
4.3%
d1
 
4.3%
1
 
4.3%
Other values (2)2
 
8.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter18
78.3%
Uppercase Letter4
 
17.4%
Space Separator1
 
4.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a5
27.8%
n3
16.7%
t3
16.7%
p2
 
11.1%
e2
 
11.1%
i1
 
5.6%
d1
 
5.6%
s1
 
5.6%
Uppercase Letter
ValueCountFrequency (%)
J2
50.0%
U1
25.0%
S1
25.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin22
95.7%
Common1
 
4.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
a5
22.7%
n3
13.6%
t3
13.6%
J2
 
9.1%
p2
 
9.1%
e2
 
9.1%
U1
 
4.5%
i1
 
4.5%
d1
 
4.5%
S1
 
4.5%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII23
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a5
21.7%
n3
13.0%
t3
13.0%
J2
 
8.7%
p2
 
8.7%
e2
 
8.7%
U1
 
4.3%
i1
 
4.3%
d1
 
4.3%
1
 
4.3%
Other values (2)2
 
8.7%

_embedded.show.network.country.code
Categorical

HIGH CORRELATION
MISSING

Distinct2
Distinct (%)66.7%
Missing46
Missing (%)93.9%
Memory size520.0 B
JP
US

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters6
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)33.3%

Sample

1st rowJP
2nd rowJP
3rd rowUS

Common Values

ValueCountFrequency (%)
JP2
 
4.1%
US1
 
2.0%
(Missing)46
93.9%

Length

2022-09-05T21:45:42.163445image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:45:42.242067image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
jp2
66.7%
us1
33.3%

Most occurring characters

ValueCountFrequency (%)
J2
33.3%
P2
33.3%
U1
16.7%
S1
16.7%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter6
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
J2
33.3%
P2
33.3%
U1
16.7%
S1
16.7%

Most occurring scripts

ValueCountFrequency (%)
Latin6
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
J2
33.3%
P2
33.3%
U1
16.7%
S1
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII6
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
J2
33.3%
P2
33.3%
U1
16.7%
S1
16.7%

_embedded.show.network.country.timezone
Categorical

HIGH CORRELATION
MISSING

Distinct2
Distinct (%)66.7%
Missing46
Missing (%)93.9%
Memory size520.0 B
Asia/Tokyo
America/New_York

Length

Max length16
Median length10
Mean length12
Min length10

Characters and Unicode

Total characters36
Distinct characters17
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)33.3%

Sample

1st rowAsia/Tokyo
2nd rowAsia/Tokyo
3rd rowAmerica/New_York

Common Values

ValueCountFrequency (%)
Asia/Tokyo2
 
4.1%
America/New_York1
 
2.0%
(Missing)46
93.9%

Length

2022-09-05T21:45:42.318828image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-09-05T21:45:42.406048image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
asia/tokyo2
66.7%
america/new_york1
33.3%

Most occurring characters

ValueCountFrequency (%)
o5
13.9%
A3
 
8.3%
i3
 
8.3%
a3
 
8.3%
/3
 
8.3%
k3
 
8.3%
e2
 
5.6%
r2
 
5.6%
y2
 
5.6%
s2
 
5.6%
Other values (7)8
22.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter25
69.4%
Uppercase Letter7
 
19.4%
Other Punctuation3
 
8.3%
Connector Punctuation1
 
2.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o5
20.0%
i3
12.0%
a3
12.0%
k3
12.0%
e2
 
8.0%
r2
 
8.0%
y2
 
8.0%
s2
 
8.0%
m1
 
4.0%
c1
 
4.0%
Uppercase Letter
ValueCountFrequency (%)
A3
42.9%
T2
28.6%
N1
 
14.3%
Y1
 
14.3%
Other Punctuation
ValueCountFrequency (%)
/3
100.0%
Connector Punctuation
ValueCountFrequency (%)
_1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin32
88.9%
Common4
 
11.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
o5
15.6%
A3
9.4%
i3
9.4%
a3
9.4%
k3
9.4%
e2
 
6.2%
r2
 
6.2%
y2
 
6.2%
s2
 
6.2%
T2
 
6.2%
Other values (5)5
15.6%
Common
ValueCountFrequency (%)
/3
75.0%
_1
 
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII36
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o5
13.9%
A3
 
8.3%
i3
 
8.3%
a3
 
8.3%
/3
 
8.3%
k3
 
8.3%
e2
 
5.6%
r2
 
5.6%
y2
 
5.6%
s2
 
5.6%
Other values (7)8
22.2%

_embedded.show.network.officialSite
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing49
Missing (%)100.0%
Memory size520.0 B

_embedded.show.webChannel
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing49
Missing (%)100.0%
Memory size520.0 B

Interactions

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2022-09-05T21:45:32.765037image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Correlations

2022-09-05T21:45:42.498843image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2022-09-05T21:45:42.741353image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2022-09-05T21:45:42.966358image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2022-09-05T21:45:43.232081image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2022-09-05T21:45:33.854283image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2022-09-05T21:45:34.479779image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.
2022-09-05T21:45:34.897545image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

Sample

First rows

idurlnameseasonnumbertypeairdateairtimeairstampruntimeimagesummaryrating.average_links.self.href_embedded.show.id_embedded.show.url_embedded.show.name_embedded.show.type_embedded.show.language_embedded.show.genres_embedded.show.status_embedded.show.runtime_embedded.show.averageRuntime_embedded.show.premiered_embedded.show.ended_embedded.show.officialSite_embedded.show.schedule.time_embedded.show.schedule.days_embedded.show.rating.average_embedded.show.weight_embedded.show.network_embedded.show.webChannel.id_embedded.show.webChannel.name_embedded.show.webChannel.country.name_embedded.show.webChannel.country.code_embedded.show.webChannel.country.timezone_embedded.show.webChannel.officialSite_embedded.show.dvdCountry_embedded.show.externals.tvrage_embedded.show.externals.thetvdb_embedded.show.externals.imdb_embedded.show.image.medium_embedded.show.image.original_embedded.show.summary_embedded.show.updated_embedded.show._links.self.href_embedded.show._links.previousepisode.hrefimage.mediumimage.original_embedded.show._links.nextepisode.href_embedded.show.image_embedded.show.webChannel.country_embedded.show.network.id_embedded.show.network.name_embedded.show.network.country.name_embedded.show.network.country.code_embedded.show.network.country.timezone_embedded.show.network.officialSite_embedded.show.webChannel
01988862https://www.tvmaze.com/episodes/1988862/sim-for-you-4x24-chanyeols-episode-24Chanyeol's Episode 24424regular2020-12-1906:002020-12-18T21:00:00+00:0016.0NaN<p><b>#VacanceAlbumRelease #Thisistheend #(There'sacookie)</b></p>NaNhttps://api.tvmaze.com/episodes/198886241648https://www.tvmaze.com/shows/41648/sim-for-youSim for YouRealityKorean[]Running16.016.02019-03-25Nonehttps://www.vlive.tv/video/121637[Monday, Wednesday, Friday]NaN29NaN122.0V LIVEKorea, Republic ofKRAsia/Seoulhttps://www.vlive.tv/homeNoneNaN361541.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/190/476668.jpghttps://static.tvmaze.com/uploads/images/original_untouched/190/476668.jpg<p><b>Sim for You</b> is a reality series that chronicles each EXO member's life and reveal stories from their everyday life as a series.</p>1608499007https://api.tvmaze.com/shows/41648https://api.tvmaze.com/episodes/1988862NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
11989501https://www.tvmaze.com/episodes/1989501/troe-iz-prostokvasino-2x39-papa-ne-gorujПапа, не горюй239regular2020-12-192020-12-19T00:00:00+00:0019.0NaNNoneNaNhttps://api.tvmaze.com/episodes/198950110892https://www.tvmaze.com/shows/10892/troe-iz-prostokvasinoТрое из ПростоквашиноAnimationRussian[Children, Family]Running7.014.01978-06-10Nonehttps://okko.tv/serial/prostokvashino12:00[]7.589NaN366.0OkkoRussian FederationRUAsia/KamchatkaNoneNoneNaN255564.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/51/128137.jpghttps://static.tvmaze.com/uploads/images/original_untouched/51/128137.jpgNone1662063139https://api.tvmaze.com/shows/10892https://api.tvmaze.com/episodes/2382770https://static.tvmaze.com/uploads/images/medium_landscape/290/726419.jpghttps://static.tvmaze.com/uploads/images/original_untouched/290/726419.jpgNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
21989503https://www.tvmaze.com/episodes/1989503/troe-iz-prostokvasino-2x40-sneznyj-labirintСнежный лабиринт240regular2020-12-192020-12-19T00:00:00+00:0019.0NaNNoneNaNhttps://api.tvmaze.com/episodes/198950310892https://www.tvmaze.com/shows/10892/troe-iz-prostokvasinoТрое из ПростоквашиноAnimationRussian[Children, Family]Running7.014.01978-06-10Nonehttps://okko.tv/serial/prostokvashino12:00[]7.589NaN366.0OkkoRussian FederationRUAsia/KamchatkaNoneNoneNaN255564.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/51/128137.jpghttps://static.tvmaze.com/uploads/images/original_untouched/51/128137.jpgNone1662063139https://api.tvmaze.com/shows/10892https://api.tvmaze.com/episodes/2382770https://static.tvmaze.com/uploads/images/medium_landscape/290/726420.jpghttps://static.tvmaze.com/uploads/images/original_untouched/290/726420.jpgNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
31988697https://www.tvmaze.com/episodes/1988697/soul-land-7x05-di135ji第135集75regular2020-12-1910:002020-12-19T02:00:00+00:0020.0NaNNoneNaNhttps://api.tvmaze.com/episodes/198869735551https://www.tvmaze.com/shows/35551/soul-landSoul LandAnimationChinese[Action, Adventure, Anime, Fantasy]Running20.020.02018-01-13Nonehttps://v.qq.com/detail/m/m441e3rjq9kwpsc.html10:00[Saturday]7.791NaN104.0Tencent QQChinaCNAsia/Shanghaihttps://v.qq.com/NoneNaN342329.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/150/375304.jpghttps://static.tvmaze.com/uploads/images/original_untouched/150/375304.jpg<p>Tang San spent his life in the Tang Outer Sect, dedicated to the creation and mastery of hidden weapons. Once he stole the secret lore of the Inner Sect to reach the pinnacle of his art, his only way out was death. But after throwing himself off the deadly Hell's Peak he was reborn in a different world, the world of Douluo Dalu, a world where every person has a spirit of their own, and those with powerful spirits can practice their spirit power to rise and become Spirit Masters.<br /><br />The spirit that awakens within Tang San is Blue Silver Grass, a useless spirit. Can he overcome the difficulties to reach the high ranks of Spirit Masters and bring the glory of the Tang Sect into this new world?</p>1652939782https://api.tvmaze.com/shows/35551https://api.tvmaze.com/episodes/2330393NaNNaNhttps://api.tvmaze.com/episodes/2330394NaNNaNNaNNaNNaNNaNNaNNaNNaN
42386108https://www.tvmaze.com/episodes/2386108/xian-feng-jian-yu-lu-1x49-episode-49Episode 49149regular2020-12-1910:002020-12-19T02:00:00+00:008.0NaNNoneNaNhttps://api.tvmaze.com/episodes/238610849206https://www.tvmaze.com/shows/49206/xian-feng-jian-yu-luXian Feng Jian Yu LuAnimationChinese[Action, Anime, Fantasy, Supernatural]Running8.07.02020-07-11Nonehttps://v.qq.com/detail/m/mzc00200hc38s5x.html10:00[Wednesday, Saturday]NaN62NaN104.0Tencent QQChinaCNAsia/Shanghaihttps://v.qq.com/NoneNaN386423.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/270/675333.jpghttps://static.tvmaze.com/uploads/images/original_untouched/270/675333.jpg<p>In ancient Shenzhou, humans and demons had been in constant dispute for thousands of years. The demon princess from Tushan, Bai Binglan, and the human Zhang Kuangyun met each other due to a misunderstanding. In order to investigate the enemy country, Bai Binglan became Zhang Kuangyun's companion. As they travel together, Zhang Kuangyun discovers a conspiracy...</p>1662275668https://api.tvmaze.com/shows/49206https://api.tvmaze.com/episodes/2386129NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
52138926https://www.tvmaze.com/episodes/2138926/tokyo-joshi-pro-wrestling-2020-12-19-tjpw-seno-merry-christmas-2020TJPW Se~No Merry Christmas! 2020202044regular2020-12-1912:002020-12-19T03:00:00+00:00120.0NaNNoneNaNhttps://api.tvmaze.com/episodes/213892649740https://www.tvmaze.com/shows/49740/tokyo-joshi-pro-wrestlingTokyo Joshi Pro WrestlingSportsJapanese[]Running120.0120.02013-01-30Nonehttps://www.ddtpro.com/12:00[Saturday]NaN46NaN408.0DDTUniverseJapanJPAsia/TokyoNoneNoneNaN375304.0tt10784214https://static.tvmaze.com/uploads/images/medium_portrait/268/670796.jpghttps://static.tvmaze.com/uploads/images/original_untouched/268/670796.jpgNone1661106712https://api.tvmaze.com/shows/49740https://api.tvmaze.com/episodes/2377377NaNNaNhttps://api.tvmaze.com/episodes/2377378NaNNaNNaNNaNNaNNaNNaNNaNNaN
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71972571https://www.tvmaze.com/episodes/1972571/the-wolf-1x29-episode-29Episode 29129regular2020-12-192020-12-19T04:00:00+00:0045.0NaNNoneNaNhttps://api.tvmaze.com/episodes/197257147912https://www.tvmaze.com/shows/47912/the-wolfThe WolfScriptedChinese[Drama, Romance, History]Ended45.045.02020-11-192021-01-04https://www.iqiyi.com/lib/m_213579814.html[]NaN38NaN118.0YoukuChinaCNAsia/ShanghaiNoneNoneNaN331095.0tt8871128https://static.tvmaze.com/uploads/images/medium_portrait/255/639532.jpghttps://static.tvmaze.com/uploads/images/original_untouched/255/639532.jpg<p>The story happens at the end of the Tang Dynasty, when Zhu Wen usurps the throne and establishes the Later Liang Dynasty, and he's known as Emperor Taizu. Ma Zhai Xing (Li Qin) is the daughter of an official and as a child, she befriends a young boy (Darren Wang) who lives in the mountain. One day when he saves a wolf, he accidentally falls over the cliff and is rescued by Zhu Wen. The authoritative figure adopts him as a godson and gives him the title Bo Wang. Ten years later, he saves the female lead per chance and finds her courage and intelligence resonant, and she likes that while he's in a position of power, he still has humility and kindness. She encourages him to fight for justice and he begins that journey by helping the people, stopping throne fights, etc. Even when they have conflicts, they will face those frankly. As they overcome obstacles and fight for justice, feelings deepen and they are able to reap their own happiness by each other's side.</p>1648217029https://api.tvmaze.com/shows/47912https://api.tvmaze.com/episodes/1972591NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
81972572https://www.tvmaze.com/episodes/1972572/the-wolf-1x30-episode-30Episode 30130regular2020-12-192020-12-19T04:00:00+00:0045.0NaNNoneNaNhttps://api.tvmaze.com/episodes/197257247912https://www.tvmaze.com/shows/47912/the-wolfThe WolfScriptedChinese[Drama, Romance, History]Ended45.045.02020-11-192021-01-04https://www.iqiyi.com/lib/m_213579814.html[]NaN38NaN118.0YoukuChinaCNAsia/ShanghaiNoneNoneNaN331095.0tt8871128https://static.tvmaze.com/uploads/images/medium_portrait/255/639532.jpghttps://static.tvmaze.com/uploads/images/original_untouched/255/639532.jpg<p>The story happens at the end of the Tang Dynasty, when Zhu Wen usurps the throne and establishes the Later Liang Dynasty, and he's known as Emperor Taizu. Ma Zhai Xing (Li Qin) is the daughter of an official and as a child, she befriends a young boy (Darren Wang) who lives in the mountain. One day when he saves a wolf, he accidentally falls over the cliff and is rescued by Zhu Wen. The authoritative figure adopts him as a godson and gives him the title Bo Wang. Ten years later, he saves the female lead per chance and finds her courage and intelligence resonant, and she likes that while he's in a position of power, he still has humility and kindness. She encourages him to fight for justice and he begins that journey by helping the people, stopping throne fights, etc. Even when they have conflicts, they will face those frankly. As they overcome obstacles and fight for justice, feelings deepen and they are able to reap their own happiness by each other's side.</p>1648217029https://api.tvmaze.com/shows/47912https://api.tvmaze.com/episodes/1972591NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
92071487https://www.tvmaze.com/episodes/2071487/youths-in-the-breeze-1x17-full-time-sworn-enemy-01FULL-TIME SWORN ENEMY #01117regular2020-12-192020-12-19T04:00:00+00:007.0NaNNoneNaNhttps://api.tvmaze.com/episodes/207148754762https://www.tvmaze.com/shows/54762/youths-in-the-breezeYouths in the BreezeScriptedChinese[Drama, Fantasy]Ended7.07.02020-12-132020-12-22https://v.youku.com/v_show/id_XNDk4OTUxMzg1Mg==.html?spm=a2hbt.13141534.0.13141534&s=6eefbfbd4befbfbd32ef[Monday, Tuesday, Wednesday, Thursday, Friday, Saturday, Sunday]NaN27NaN118.0YoukuChinaCNAsia/ShanghaiNoneNoneNaN397247.0Nonehttps://static.tvmaze.com/uploads/images/medium_portrait/308/770106.jpghttps://static.tvmaze.com/uploads/images/original_untouched/308/770106.jpg<p>The play consists of three youth stories. "He and Meow": The cat Jiang Xiao Kui and his owner Jiang Qing from the cat kingdom live a happy life. Until Jiang Qing's younger brother Jiang Xia returned home. Xia, who was allergic to cats, and Jiang Xiao Kui, who hated his younger brother, started a battle over sister's favor. "Full-time rival": Xu Tian Yi and Li Shi Lin, who had been at odds for a long time, reunited during the summer sprint training. In the process of competing against each other, their misunderstanding was resolved. Just when the two worked together to enter the team, an accident happened. "The Man in the Story": Yu Sheng, a young man, accidentally discovered that he turned out to be a character in Xu Mo's novel. After learning about the tragic ending of himself and his sister, he came to the real world to fight with the writer in an attempt to change his destiny.</p><p><br /> </p>1618466682https://api.tvmaze.com/shows/54762https://api.tvmaze.com/episodes/2071494NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN

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431988690https://www.tvmaze.com/episodes/1988690/um-actually-4x10-magic-the-gatheringMagic: the Gathering410regular2020-12-192020-12-19T17:00:00+00:0030.0NaNNoneNaNhttps://api.tvmaze.com/episodes/198869050839https://www.tvmaze.com/shows/50839/um-actuallyUm, Actually...Game ShowEnglish[]Running30.030.02018-09-28NoneNone[]NaN73NaN228.0CollegehumorUnited StatesUSAmerica/New_YorkNoneNoneNaN356085.0tt9690112https://static.tvmaze.com/uploads/images/medium_portrait/275/689839.jpghttps://static.tvmaze.com/uploads/images/original_untouched/275/689839.jpg<p>Introducing a game show of fandom minutiae one-upmanship, where nerds do what nerds do best: flaunt encyclopedic nerd knowledge at Millennium Falcon nerd-speed.</p>1661698147https://api.tvmaze.com/shows/50839https://api.tvmaze.com/episodes/2381563NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
441943281https://www.tvmaze.com/episodes/1943281/rail-romanesque-1x12-departure-onwardsDeparture! Onwards!112regular2020-12-192020-12-19T17:00:00+00:005.0NaNNoneNaNhttps://api.tvmaze.com/episodes/194328150939https://www.tvmaze.com/shows/50939/rail-romanesqueRail RomanesqueAnimationJapanese[Comedy, Anime, Science-Fiction]Ended5.05.02020-10-032020-12-19https://railromanesque.jp[Saturday]NaN48NaN20.0CrunchyrollNaNNaNNaNNoneNoneNaN386577.0tt12584900https://static.tvmaze.com/uploads/images/medium_portrait/276/691347.jpghttps://static.tvmaze.com/uploads/images/original_untouched/276/691347.jpg<p>Set in Hinomoto, a fictional version of Japan, where for a long time railway travel served as the most important form of transport. Each locomotive was paired with a humanoid control module, so-called Raillord, that aided the train operator. However, many rail lines had been discontinued due to the rising popularity of "aerocrafts," a safe and convenient aerial mode of transport. As such, their accompanying railroads also went into a deep sleep. Soutetsu had lost his entire family in a rail accident and was adopted into the Migita household, which runs a shochu brewery in the city of Ohitoyo. He returned to his hometown to save it from the potential water pollution that would occur if they accepted the proposal to build an aerocraft factory nearby. He woke up the Raillord Hachiroku by accident and became her owner. For different purposes, they agreed to help find her lost locomotive, with the help of his stepsister Hibiki, the town's mayor and local railway chief, Paulette and others.</p>1645753159https://api.tvmaze.com/shows/50939https://api.tvmaze.com/episodes/1943281NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
452037520https://www.tvmaze.com/episodes/2037520/lovely-bites-by-chef-lovely-1x06-dinner-made-with-loveDinner Made with Love16regular2020-12-192020-12-19T17:00:00+00:0025.0NaN<p>Chef Lovely creates an elegant dinner for close friends. She makes her Roasted Chicken with Pomegranate Glaze, Green Beans Over Lemon Ricotta and Sweet Potato and Gruyere Gratin. Plus, there's an Upside-Down Pear Tart for dessert. You can taste the love!</p>NaNhttps://api.tvmaze.com/episodes/203752053754https://www.tvmaze.com/shows/53754/lovely-bites-by-chef-lovelyLovely Bites by Chef LovelyRealityEnglish[]Running25.025.02020-11-14Nonehttps://www.oprah.com/app/lovely-bites.html[]NaN19NaNNaNNaNNaNNaNNaNNaNNoneNaN394876.0tt13399538https://static.tvmaze.com/uploads/images/medium_portrait/297/744528.jpghttps://static.tvmaze.com/uploads/images/original_untouched/297/744528.jpg<p>Chef Connie "Lovely" Jackson brings the fun with recipes that are perfect for entertaining and celebrating festive occasions. <b>Lovely Bites</b> is produced for OWN by FishBowl Worldwide Media.</p>1623829529https://api.tvmaze.com/shows/53754https://api.tvmaze.com/episodes/2113588https://static.tvmaze.com/uploads/images/medium_landscape/329/823876.jpghttps://static.tvmaze.com/uploads/images/original_untouched/329/823876.jpgNaNNaNNaN236.0Oprah Winfrey NetworkUnited StatesUSAmerica/New_YorkNaNNaN
461983274https://www.tvmaze.com/episodes/1983274/eides-spraksjov-6x05-gudbrandsdalen-avdeling-tromsGudbrandsdalen, avdeling Troms65regular2020-12-1921:502020-12-19T20:50:00+00:0050.0NaNNoneNaNhttps://api.tvmaze.com/episodes/198327451631https://www.tvmaze.com/shows/51631/eides-spraksjovEides språksjovTalk ShowNorwegian[Comedy]RunningNaN43.02017-01-11Nonehttps://tv.nrk.no/serie/eides-spraaksjov[Saturday]NaN4NaN238.0NRK TVNorwayNOEurope/OsloNoneNoneNaN322906.0tt8851444https://static.tvmaze.com/uploads/images/medium_portrait/280/701389.jpghttps://static.tvmaze.com/uploads/images/original_untouched/280/701389.jpg<p>Entertainment from here to the moon when Linda Eide and guests pay tribute and joke with language.</p>1650016918https://api.tvmaze.com/shows/51631https://api.tvmaze.com/episodes/2297850NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
471984914https://www.tvmaze.com/episodes/1984914/onyx-equinox-1x05-predationPredation15regular2020-12-1916:002020-12-19T21:00:00+00:0024.0NaN<p>As the group heads for Danibaan, one of them suffers a horrifying injury. With nowhere left to turn, they seek help from a mysterious healer.</p>8.0https://api.tvmaze.com/episodes/198491448922https://www.tvmaze.com/shows/48922/onyx-equinoxOnyx EquinoxAnimationEnglish[Action, Adventure, Fantasy]Ended24.024.02020-11-212020-12-26https://www.crunchyroll.com/onyx-equinox16:00[Saturday]5.046NaN20.0CrunchyrollNaNNaNNaNNoneNoneNaN377625.0tt12605636https://static.tvmaze.com/uploads/images/medium_portrait/263/658930.jpghttps://static.tvmaze.com/uploads/images/original_untouched/263/658930.jpg<p>A young Aztec boy is saved from death by the gods and chosen to act as ‘humanity's champion,' forced to discard his apathy toward his fellow man and prove humanity's potential in a fight that spans across fantastical-yet-authentic Mesoamerican cultures.</p>1609359827https://api.tvmaze.com/shows/48922https://api.tvmaze.com/episodes/1990352NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
481984187https://www.tvmaze.com/episodes/1984187/ufc-fight-night-2020-12-19-ufc-fight-night-183-thompson-vs-nealUFC Fight Night 183: Thompson vs. Neal202030regular2020-12-1922:002020-12-20T03:00:00+00:00335.0NaNNoneNaNhttps://api.tvmaze.com/episodes/19841871596https://www.tvmaze.com/shows/1596/ufc-fight-nightUFC Fight NightSportsEnglish[]Running120.0194.02005-08-06Nonehttp://www.ufc.com/22:00[Saturday]7.795NaN265.0ESPN+United StatesUSAmerica/New_YorkNoneNone15090.0NaNNonehttps://static.tvmaze.com/uploads/images/medium_portrait/293/734642.jpghttps://static.tvmaze.com/uploads/images/original_untouched/293/734642.jpg<p><b>UFC Fight Night</b> is a part of the Ultimate Fighting Championship (UFC) which is the largest mixed martial arts promotion company in the world featuring most of the top-ranked fighters in the sport. Based in the United States, the UFC produces events worldwide. The organization showcases nine weight divisions and abides by the Unified Rules of Mixed Martial Arts. The UFC has held over 300 events to date. Dana White serves as the president of the UFC while brothers Frank and Lorenzo Fertitta control the UFC's parent company, Zuffa, LLC. The first UFC event was held on November 12, 1993 at the McNichols Sports Arena in Denver, Colorado. The purpose of the early UFC competitions was to identify the most effective martial art in a real fight between competitors of different fighting disciplines, including boxing, Brazilian jiu-jitsu, Sambo, wrestling, Muay Thai, karate, judo, and other styles. In subsequent competitions, fighters began adopting effective techniques from more than one discipline, which indirectly helped create an entirely separate style of fighting known as present-day mixed martial arts.</p>1661666143https://api.tvmaze.com/shows/1596https://api.tvmaze.com/episodes/2343874https://static.tvmaze.com/uploads/images/medium_landscape/288/721046.jpghttps://static.tvmaze.com/uploads/images/original_untouched/288/721046.jpghttps://api.tvmaze.com/episodes/2343875NaNNaNNaNNaNNaNNaNNaNNaNNaN